Parallax Momentum MNQ Strategy# 📈 Parallax Momentum MNQ Strategy
## Overview
The Parallax Momentum MNQ Strategy is a sophisticated support/resistance breakout system specifically designed for Micro Nasdaq futures (MNQ) trading (also works on minis). This strategy combines dynamic level detection with momentum confirmation to identify high-probability entry opportunities while maintaining strict risk management protocols.
## 🎯 Key Features
### Core Strategy Logic
- **Dynamic Support/Resistance Detection**: Automatically identifies key levels using configurable lookback periods
- **Momentum Confirmation**: Volume-based filtering ensures trades align with market momentum
- **ATR-Based Risk Management**: Adaptive stop losses and take profits based on market volatility
- **Dual Entry System**: Both long and short opportunities with limit order execution
### Risk Management
- **ATR-Adaptive Stops**: Stop losses and take profits automatically adjust to market volatility
- **Reward-to-Risk Ratios**: Configurable R:R ratios with default 2:1 minimum
- **Maximum Loss Protection**: Optional daily loss limits to prevent overtrading
- **Session Time Filtering**: Trade only during specified market hours
### Strategy Modes
- **Conservative Mode**: 0.8x risk multiplier for cautious trading
- **Balanced Mode**: Standard 1.0x risk multiplier (default)
- **Aggressive Mode**: 1.2x risk multiplier for active trading
## 📊 Visual Features
### Dashboard Display
- Real-time strategy status and performance metrics
- Current support/resistance levels and ATR values
- Live risk-to-reward ratios for potential trades
- Win rate, profit factor, and drawdown statistics
- Adjustable dashboard size and positioning
### Chart Indicators
- Support and resistance lines with labels
- ATR-based levels (+/-1 ATR and +/-2 ATR)
- Dynamic visual updates as levels change
- Configurable line extensions and styling
## ⚙️ Configuration Options
### Entry Filters
- **Volume Filter**: Optional volume confirmation above SMA
- **Session Time Filter**: 12-hour format time restrictions
- **ATR vs Fixed Stops**: Choose between adaptive or fixed tick-based exits
### Risk Controls
- **ATR Period**: Default 14-period ATR calculation
- **Stop Loss Multiplier**: ATR-based stop distance (default 1.5x)
- **Take Profit Multiplier**: ATR-based target distance (default 1.5x)
- **Secondary Take Profit**: Optional TP2 with position scaling
## 📋 How It Works
### Entry Conditions
**Long Trades**: Triggered when price closes above support buffer but low touches support level, with volume and session confirmation
**Short Trades**: Triggered when price closes below resistance buffer but high touches resistance level, with volume and session confirmation
### Exit Strategy
- **Primary Take Profit**: ATR-based target with 2:1 R:R minimum
- **Stop Loss**: ATR-based protective stop
- **Optional TP2**: Extended target for partial profit taking
- **One Trade at a Time**: No overlapping positions
## 🎛️ Default Settings
- **Lookback Period**: 20 bars for support/resistance detection
- **ATR Period**: 14 bars for volatility calculation
- **Stop Loss**: 1.5x ATR from entry
- **Take Profit**: 1.5x ATR with 2:1 reward-to-risk ratio
- **Session**: 7:30 AM - 2:00 PM (configurable)
## ⚠️ Important Notes
### Risk Disclaimer
- This strategy is for educational and informational purposes only
- Past performance does not guarantee future results
- Always use proper position sizing and risk management
- Test thoroughly on historical data before live trading
- Consider market conditions and volatility when using
### Best Practices
- Backtest on sufficient historical data
- Start with conservative mode for new users
- Monitor performance regularly and adjust parameters as needed
- Use appropriate position sizing for your account
- Consider broker commissions and slippage in live trading
## 🔧 Customization
The strategy offers extensive customization options including:
- Adjustable time sessions with AM/PM format
- Configurable ATR and risk parameters
- Optional maximum daily loss limits
- Dashboard size and position controls
- Visual element toggles and styling
## 📈 Ideal For
- MNQ (Micro Nasdaq) futures traders
- Intraday momentum strategies
- Traders seeking systematic entry/exit rules
- Risk-conscious traders wanting automated stops
- Both beginner and experienced algorithmic traders
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**Version**: Pine Script v5 Compatible
**Timeframe**: Works on multiple timeframes (test on 1m, 3m, 5m, 15m)
**Market**: Optimized for MNQ but adaptable to other instruments
**Strategy Type**: Trend following with momentum confirmation
ATR
ATR Squeeze BackgroundThis simple but powerful indicator shades the background of your chart whenever volatility contracts, based on a custom comparison of fast and slow ATR (Average True Range) periods.
By visualizing low-volatility zones, you can:
* Identify moments of compression that may precede explosive price moves
* Stay out of choppy, low-momentum periods
* Adapt this as a component in a broader volatility or breakout strategy
🔧 How It Works
* A Fast ATR (default: 7 periods) and a Slow ATR (default: 40 periods) are calculated
* When the Fast ATR is lower than the Slow ATR, the background is shaded in blue
* This shading signals a contraction in volatility — a condition often seen before breakouts or strong directional moves
⚡️ Why This Matters
Many experienced traders pay close attention to volatility cycles. This background indicator helps visualize those cycles at a glance. It's minimal, non-intrusive, and easy to combine with your existing tools.
🙏 Credits
This script borrows core logic from the excellent “Relative Volume at Time” script by TradingView. Credit is given with appreciation.
⚠️ Disclaimer
This script is for educational purposes only.
It does not constitute financial advice, and past performance is not indicative of future results. Always do your own research and test strategies before making trading decisions.
ATR % Line from LoD/HoDATR % Line Trading Indicator - Entry Filter Tool
This Pine Script creates a sophisticated ATR (Average True Range) percentage-based entry filter indicator for TradingView that helps traders avoid buying overextended stocks and identify optimal entry zones based on volatility.
Core Functionality - Entry Discipline
The script calculates a maximum entry threshold by taking a percentage of the Average True Range (ATR) and projecting it from the current day's low. This creates a dynamic "no-buy zone" that adapts to market volatility, helping traders avoid purchasing stocks that have already moved too far from their daily base.
Key Calculation:
Measures the ATR over a specified period (default: 14 bars)
Takes a user-defined percentage of that ATR (default: 25%)
Projects this distance from the day's low to establish a maximum entry threshold
Entry Rule: Avoid buying when price exceeds this ATR% level from the daily low or high.
Visual Features
Entry Threshold Line:
Draws a horizontal line at the calculated maximum entry level
Line extends forward for clear visualization of the "no-buy zone"
Red zones above this line indicate overextended conditions
Fully customizable appearance with color, width, and style options
Smart Entry Alerts:
Optional labels show the ATR percentage threshold and exact price level
Visual confirmation when stocks are trading in acceptable entry zones vs. extended areas
Real-Time Monitoring Table:
Displays current distance from daily low as ATR percentage
Shows whether current price is in "safe entry zone" or "extended territory"
Customizable display options for clean chart analysis
Practical Applications for Entry Management
Avoiding Extended Entries:
Primary Use: Don't initiate long positions when price is more than X% ATR from the daily low
Prevents buying stocks that have already made their daily move
Reduces risk of buying at temporary tops within the trading session
Entry Zone Identification:
Price trading below the ATR% line = potential entry opportunity
Price trading above the ATR% line = wait for pullback or skip the trade
Combines volatility analysis with momentum discipline
Risk Management Benefits:
Improved Entry Timing: Enter closer to daily support levels
Better Risk/Reward: Shorter distance to stop loss (daily low)
Reduced Chasing: Systematic approach prevents FOMO-driven entries
Volatility Awareness: Higher volatility stocks get wider acceptable entry ranges
Configuration for Entry Filtering
Key Settings for Entry Management:
ATR Percentage: Set your maximum acceptable extension (15-30% common for day trading)
Reference Point: Use "Low" to measure extension from daily base
Line Style: Make highly visible to clearly see entry threshold
Alert Integration: Visual confirmation of entry-friendly zones
Typical Usage Scenarios:
Conservative Entries: 15-20% ATR from daily low
Moderate Extensions: 25-35% ATR for stronger momentum plays
Aggressive Setups: 40%+ ATR for breakout situations (use with caution)
Entry Strategy Integration
Pre-Market Planning:
Set ATR% threshold based on stock's typical volatility
Identify key levels where entries become unfavorable
Plan alternative entry strategies for extended stocks
Intraday Execution:
Monitor real-time ATR% extension from daily low
Avoid new long positions when threshold is exceeded
Wait for pullbacks to re-enter acceptable entry zones
This tool transforms volatility analysis into practical entry discipline, helping traders maintain consistent entry standards and avoid the costly mistake of chasing overextended stocks. By respecting ATR-based extension limits, traders can improve their entry timing and overall trade profitability.
ATR Plots + OverlayATR Plots + Overlay
This tool calculates and displays Average True Range (ATR)-based levels on your chart for any selected timeframe, giving traders a quick visual reference for expected price movement relative to the most recent bar’s open price. It plots guide levels above and below that open and shows how much of the typical ATR-based range has already been covered—all in one interactive table and on-chart overlay.
What It Does
ATR Calculation:
Uses true range data over a user-defined period (default 14), smoothed via RMA, SMA, EMA, or WMA, on the selected timeframe (e.g., 1h, 4h, daily) to calculate the ATR value.
Projected Levels:
Plots four reference levels relative to the open price of the most recent bar on the chosen timeframe:
+100% ATR: Open + ATR
+50% ATR: Open + 50% of ATR
−50% ATR: Open − 50% of ATR
−100% ATR: Open − ATR
Coverage %:
Tracks high and low prices for the current session on the selected timeframe and calculates what percentage of the ATR has already been covered:
Coverage % = (High − Low) ÷ ATR × 100
Interactive Table:
Shows the ATR value and current coverage percentage in a customizable table overlay. Position, color scheme, borders, transparency, and an optional empty top row are all adjustable via settings.
Customization Options
Table Settings:
Position the table (top/bottom × left/right).
Customize background color, text color, border color, and thickness.
Optionally add an empty top row for spacing.
Line Settings:
Choose color, line style (solid/dotted/dashed), and width.
Lines automatically update with each new bar on the selected timeframe, anchored to that bar’s open price.
General Inputs:
ATR length (number of bars).
Smoothing method (RMA, SMA, EMA, WMA).
Timeframe selection for ATR calculations (e.g., 15m, 1h, Daily).
How to Use It for Trading
Measure Volatility: Quickly gauge the expected price movement based on ATR for any timeframe.
Identify Overextension: Use the coverage % to see how much of the expected ATR range is already consumed.
Plan Entries & Exits: Align trade targets and stops with ATR levels for more objective planning.
Visual Reference: Horizontal guide lines and table update automatically as new bars form, keeping information clear and actionable.
Ideal For
Intraday traders using ATR levels to frame trades.
Swing traders wanting ATR-based reference points for larger timeframes.
Anyone seeking a volatility-based framework for planning stops, targets, or identifying overextended conditions.
Combined Predictive Indicator### Combined Predictive Zones & Levels
This indicator is a powerful hybrid tool designed to provide a comprehensive map of potential future price action. It merges two distinct predictive models into a single, cohesive view, helping traders identify key levels of support, resistance, and areas of high confluence.
#### How It Works: Two Models in One
This script is built on two core components that you can use together or analyze separately:
**Part 1: Classic Range & Fibonacci Prediction**
This model uses classic technical analysis principles to project a potential range for the upcoming price action.
* **Highest High / Lowest Low:** It identifies the significant trading range over a user-defined lookback period.
* **Fibonacci Levels:** It automatically plots key Fibonacci retracement levels (e.g., 38.2% and 61.8%) within this range, which often act as critical support or resistance.
* **ATR & Average Range:** It calculates a "predicted" upper and lower boundary based on the average historical range and current volatility (ATR).
**Part 2: Advanced Predictive Ranges (Self-Adjusting Channels)**
This is a dynamic model that creates adaptive support and resistance zones based on a smoothed average price and volatility.
* **Dynamic Average:** It uses a unique moving average that only adjusts when the price moves significantly, creating a stable baseline.
* **ATR-Based Zones:** It projects multiple levels of support (S1, S2) and resistance (R1, R2) around this average, which widen and narrow based on market volatility. These zones often signal areas where price might stall or reverse.
#### Key Features:
* **Hybrid Model for Confluence:** The true power of this indicator lies in finding where the levels from both models overlap. A Fibonacci level aligning with a Predictive Range support zone is a much stronger signal.
* **Comprehensive Data Table:** A clean, on-chart table displays the precise values of all key predictive levels, allowing for quick reference and precise trade planning.
* **Multi-Timeframe (MTF) Capability:** The Advanced Predictive Ranges can be calculated on a higher timeframe, giving you a broader market context.
* **Fully Customizable:** All lengths, multipliers, and levels for both models are fully adjustable in the settings to fit any asset or trading style.
* **Clear Visuals:** All zones and levels are color-coded for intuitive and easy-to-read analysis.
#### How to Use:
1. Look for areas of **confluence** where multiple levels from both models cluster together. These are high-probability zones for price reactions.
2. Use the Predictive Range zones (S1/S2 and R1/R2) as potential targets for trades or as areas to watch for entries and exits.
3. Pay attention to the on-chart table for exact price levels to set limit orders or stop-losses.
**Disclaimer:** This script is an analytical tool for educational purposes and should not be considered financial advice. All trading involves risk. Past performance is not indicative of future results. Always use this indicator as part of a comprehensive trading strategy with proper risk management.
Feedback is welcome! If you find this tool useful, please leave a like.
NOMANOMA Adaptive Confidence Strategy —
What is NOMA?
NOMA is a next-generation, confidence-weighted trading strategy that fuses modern trend logic, multi-factor market structure, and adaptive risk controls—delivering a systematic edge across futures, stocks, forex, and crypto markets. Designed for precision, adaptability, and hands-off automation, NOMA provides actionable trade signals and real-time alerts so you never miss a high-conviction opportunity.
Key Benefits & Why Use NOMA?
Trade With Confidence, Not Guesswork:
NOMA combines over 11 institutional-grade confirmations (market structure, order flow, volatility, liquidity, SMC/ICT concepts, and more) into a single “confidence score” engine. Every trade entry is filtered through customizable booster weights, so only the strongest opportunities trigger.
Built-In Alerts:
Get instant notifications on all entries, take-profits, trailing stop events, and exits. Connect alerts to your mobile, email, or webhook for seamless automation or just peace of mind.
Advanced Position Management:
Supports up to 5 separate take-profit levels with adjustable quantities, plus dynamic and stepwise trailing stops. Protects your gains and adapts exit logic to market movement, not just static targets.
Anti-Chop/No Trade Zones:
Eliminate low-probability, sideways market conditions using the “No Chop Zone” filter, so you only trade in meaningful, trending environments.
Full Market Session Control:
Restrict trades to custom sessions (e.g., New York hours) for added discipline and to avoid overnight risk.
— Ideal for day traders and prop-firm requirements.
Multi-Asset & Timeframe Support:
Whether you trade micro futures, stocks, forex, or crypto, NOMA adapts its TP/SL logic to ticks, pips, or points and works on any timeframe.
How NOMA Works (Feature Breakdown)
1. Adaptive Trend Engine
Uses a custom NOMA line that blends classic moving averages with dynamic momentum and a proprietary “Confidence Momentum Oscillator” overlay.
Visual trend overlay and color fill for easy chart reading.
2. Multi-Factor Confidence Scoring
Each trade is scored on up to 11 confidence “boosters,” including:
Market Manipulation & Accumulation (detects smart money traps and true range expansions)
Accumulation/Distribution (AD line)
ATR Volatility Rank (prioritizes trades when volatility is “just right”)
COG Cross (center of gravity reversal points)
Change of Character/Break of Structure (CHoCH/BOS logic, SMC/ICT style)
Order Blocks, Breakers, FVGs, Inducements, OTE (Optimal Trade Entry) Zones
You control the minimum score required for a trade to trigger, plus the weight of each factor (customize for your asset or style).
3. Smart Trade Management
Step Take-Profits:
Up to 5 profit targets, each with individual contract/quantity splits.
Step Trailing Stop:
Trail your stop with a ratcheting logic that tightens after each TP is hit, or use a fully dynamic ATR-based trail for volatile markets.
Kill-Switch:
Instant trailing stop logic closes all open contracts if price reverses sharply.
4. Session Filter & Cooldown Logic
Restricts trading to key sessions (e.g., NY open) to avoid low-liquidity or dead zones.
Cooldown bars prevent “overtrading” or rapid re-entries after an exit.
5. Chop Zone Filter
Optionally blocks trades during flat/choppy periods using a custom “NOMA spread” calculation.
When enabled, background color highlights no-trade periods for clarity.
6. Real-Time Alerts
Receive alerts for:
Trade entries (long & short, with confidence score)
Every take-profit target hit
Trailing stop exits or full position closes
Easy setup: Create alerts for all conditions and get notified instantly.
Customization & Inputs
TP/SL Modes: Choose between manual, ATR-multiplied, or hybrid take-profit and trailing logic.
Position Sizing: Fixed contracts/quantity per trade, with customizable splits for scaling out.
Session Settings: Restrict to any time window.
Confidence Engine: User-controlled weights and minimum score—tailor for your asset.
Risk & Volatility Filters: ATR length/multiplier, min/max range, and more.
How To Use
Add NOMA to your chart.
Customize your settings (session, TPs, confidence scores, etc.).
Set up TradingView alerts (“Any Alert() function call”) to receive notifications.
Monitor trade entries, profit targets, and stops directly on your chart or in your inbox.
Adjust confidence weights as you optimize for your favorite asset.
Pro Tips
Start with default settings—they are optimized for NQ micro futures, 15m timeframe.
Increase the minimum confidence score or weights for stricter filtering in volatile or low-liquidity markets.
Adjust your take-profit and trailing stop settings to match your trading style (scalping vs. swing).
Enable “No Chop Zone” during sideways conditions for cleaner signals.
Test in strategy mode before trading live to dial in your risk and settings.
Disclaimer
This script is for educational and research purposes only. No trading system guarantees future results.
Performance will vary by symbol, timeframe, and market regime—always test settings and use at your own risk. Not investment advice.
If alerts or strategy entries are not triggering as expected, try lowering the minimum confidence score or disabling certain boosters.
This will come with a user manual please do not hesitate to message me to gain access. TO THE MOON AND BEYOND
Intelligent Moving📘 Intelligent Moving – Adaptive Neural Trend Engine
Intelligent Moving is an invite-only, closed-source indicator that dynamically adjusts itself to evolving market conditions using a built-in neural optimizer. It combines a custom adaptive Moving Average, ATR-based deviation bands, and a fully internal virtual trade simulator to deliver smart trend signals and automatic parameter tuning — all without repainting or manual intervention.
This script is built entirely from original code and does not use any open-source components or built-in TradingView indicators.
🧠 Core Logic and Visual Structure
The indicator plots:
- A central moving average (optimized dynamically),
- Upper and lower deviation bands based on ATR × adaptive coefficients,
- Buy (aqua) and Sell (orange) arrows on reversion signals,
- Color-coded trend zones based on price vs. moving average.
All three bands change color in real time depending on the price’s position relative to the MA, clearly showing uptrends (e.g. blue) and downtrends (e.g. red).
📈 Signal Logic: Reversion from Extremes
- Buy Signal: After price closes below the lower deviation band, it then closes back above it.
- Sell Signal: After price closes above the upper deviation band, it then closes back below it.
These signals are not based on crossovers, oscillators, or lagging logic — they are pure structure-based reversion entries, designed to detect exhaustion and reversal zones.
🤖 Built-In Neural Optimizer (Perceptron Engine)
At the heart of Intelligent Moving lies a self-training engine that uses simulated (virtual) positions to test multiple configurations and pick the best one. Here’s how it works:
🔄 Virtual Trade Simulation
At regular intervals (user-defined), the script:
- Simulates virtual buy/sell positions based on its signal logic.
- Applies virtual Stop-Loss (just beyond the signal zone) and virtual Take-Profit (when price crosses back over the MA).
- Calculates simulated profit for each combination of:
- - MA periods,
- - Upper/lower ATR multipliers.
🧠 Neural Training Process
- A perceptron-like engine evaluates the simulated results.
- It selects the best-performing configuration and applies it to live plotting.
- You can choose whether optimization uses a base value or the last best result from the previous training pass.
This process runs forward-only and never overwrites history or uses future data. It's completely transparent and non-repainting.
⚙️ Customization and Parameters
Users can control:
- MA period range, step, and training type (base vs last best)
- Deviation multiplier ranges and step
- Training depth (number of bars in history)
- Training interval (how often to retrain)
- Spread simulation, alert options, and all visual settings
💡 What Makes It Unique
- ✅ Self-optimization with virtual trades and perceptron logic
- ✅ Adaptive deviation bands based on ATR (not standard deviation)
- ✅ No built-in indicators, no repaints, no curve-fitting
- ✅ Clear trend zones and reversal signals
- ✅ Optimized for live use and consistent behavior across assets
Unlike typical moving average tools, Intelligent Moving thinks, adapts, and reacts — turning a standard concept into a living, learning trend engine.
📊 Use Cases
- Trend detection with adaptive coloring
- Reversion trading from volatility extremes
- Dynamic strategy building with minimal manual input
- Alerts for automated or discretionary traders
🔒 Invite-Only Notice
This script is invite-only and closed-source.
The optimization logic, trade simulation system, and perceptron engine were developed from scratch, specifically for this indicator. No built-in functions (e.g. MA, BB, RSI) or public scripts were used or copied.
All decisions and calculations are based on current and past price only — no repainting, retrofitting, or future leakage.
⚠️ Disclaimer
This indicator is for educational and analytical use only.
It does not predict future prices or guarantee profits. Always use appropriate risk management and test thoroughly before live trading.
ATR as % of CloseATR 14day period in % terms
the Normal ATR indicator by TV helps but this gives a clear idea as to the range in percentage terms as and when market rises to newer and newer highs
better than an absolute value
Fibonacci Range Detector ║ BullVision🔬 Overview
The Fibonacci Range Mapper is a dynamic technical tool designed to identify, track, and visualize price ranges using Fibonacci levels. Whether you're trading manually or prefer automated structure recognition, this indicator helps you contextualize market moves and locate key price zones with precision.
⚙️ Core Logic
🔍 Range Detection (Auto & Manual Modes)
In Auto mode, the indicator uses an advanced ZigZag system based on ATR or percentage thresholds to confirm market swings and construct Fibonacci-based ranges.
In Manual mode, traders can define their own swing low and high to generate precise custom ranges.
📐 Fibonacci Mapping
Each detected range is automatically plotted with key Fibonacci retracement levels — 0%, 25%, 50%, 75%, 100% — along with optional extensions (127.2% and 161.8%) to anticipate price continuations or reversals.
📋 Live Data Table
An integrated info panel dynamically displays crucial metrics:
• Range size
• Current price zone (Discount / Mid / Premium)
• Position within range (%)
• Distance to range extremes
• Range status (Pending or Confirmed)
🕰️ Historical Memory
Up to 20 past ranges can be stored and visualized simultaneously, helping traders recognize repeated price behaviors and contextual support/resistance levels.
🎨 Visual Highlights
Zones of interest (0–25% = Discount, 75–100% = Premium) are color-coded with custom transparency, and labels can be toggled for clarity. The current active range updates in real time as structure evolves.
🔧 User Customization
• Detection Method: Choose between ATR or % ZigZag for automated swing identification
• Confirmation Delay: Set how many bars to wait before confirming a new high
• Manual Overrides: Select exact price levels when you want full control
• Extensions & Labels: Toggle additional lines and info to suit your charting style
• Visual Table Position: Customize where the data table appears on screen
• Color Scheme: Define your own zone gradients for better visual interpretation
📈 Use Cases
This indicator is ideal for traders who want to:
• Identify value zones within local or macro price structures
• Plan trades around Fibonacci retracement and extension levels
• Detect shifts in market structure using an adaptive ZigZag logic
• Track recurring price ranges and historical reaction points
• Enhance technical confluence with clean, visual price mapping
⚠️ Important Notes
This tool is not a buy/sell signal generator — it is a visual framework for structure-based analysis.
Use it in conjunction with your existing strategy and risk management process.
Always confirm with broader context and multi-timeframe alignment.
Markov Chain Trend ProbabilityA Markov Chain is a mathematical model that predicts future states based on the current state, assuming that the future depends only on the present (not the past). Originally developed by Russian mathematician Andrey Markov, this concept is widely used in:
Finance: Risk modeling, portfolio optimization, credit scoring, algorithmic trading
Weather Forecasting: Predicting sunny/rainy days, temperature patterns, storm tracking
Here's an example of a Markov chain: If the weather is sunny, the probability that will be sunny 30 min later is say 90%. However, if the state changes, i.e. it starts raining, how the probability that will be raining 30 min later is say 70% and only 30% sunny.
Similar concept can be applied to markets price action and trends.
Mathematical Foundation
The core principle follows the Markov Property: P(X_{t+1}|X_t, X_{t-1}, ..., X_0) = P(X_{t+1}|X_t)
Transition Matrix :
-------------Next State
Current----
--------P11 P12
-----P21 P22
Probability Calculations:
P(Up→Up) = Count(Up→Up) / Count(Up states)
P(Down→Down) = Count(Down→Down) / Count(Down states)
Steady-state probability: π = πP (where π is the stationary distribution)
State Definition:
State = UPTREND if (Price_t - Price_{t-n})/ATR > threshold
State = DOWNTREND if (Price_t - Price_{t-n})/ATR < -threshold
How It Works in Trading
This indicator applies Markov Chain theory to market trends by:
Defining States: Classifies market conditions as UPTREND or DOWNTREND based on price movement relative to ATR (Average True Range)
Learning Transitions: Analyzes historical data to calculate probabilities of moving from one state to another
Predicting Probabilities: Estimates the likelihood of future trend continuation or reversal
How to Use
Parameters:
Lookback Period: Number of bars to analyze for trend detection (default: 14)
ATR Threshold: Sensitivity multiplier for state changes (default: 0.5)
Historical Periods: Sample size for probability calculations (default: 33)
Trading Applications:
Trend confirmation for entry/exit decisions
Risk assessment through probability analysis
Market regime identification
Early warning system for potential trend reversals
The indicator works on any timeframe and asset class. Enjoy!
Screener - Moving Average / ATR Breakout Signal [ARTech]Screener - Moving Average / ATR Breakout Signal
This indicator features a powerful multi-symbol screener that scans up to 40 user-defined symbols in real time for Moving Average (MA) and ATR breakout signals. Users can customize the list of symbols, select the asset class (e.g., Crypto, Stocks, Forex). The screener detects trend-following signals based on price crossing a chosen MA type and length, enhanced by optional ATR-based volatility filters and breakout thresholds to improve signal accuracy. Signals can be displayed on the chart via labels, tooltips, or a compact signal table, allowing traders to monitor multiple markets simultaneously without switching charts. The list of symbols generating signals can also be tracked with customizable alerts, enabling traders to receive real-time notifications for long and short breakout signals directly via TradingView alerts.
This indicator is developed based on the concept of Moving Average / ATR Breakout Signal script on TradingView, with enhancements to support multi-symbol scanning.
Key Features
• Multi-Symbol Screener: Scans up to 40 user-defined symbols simultaneously, with automatic separator detection and symbol validation.
• Repaint Prevention: Carefully designed to avoid repaint issues. The script structure and signal logic have been built to ensure reliable behavior, even across multiple symbols and varying chart conditions.
• Flexible Signal Display: Offers chart labels, tooltips, or a compact table to show signals, enabling multi-market monitoring without switching charts.
• Customizable Alerts: Supports alerts for both long and short signals, sending a list of symbols generating signals as real-time notifications.
• Multi-Type Moving Average Support: Choose from several MA types including EMA, SMA, Hull MA, VWMA, RMA, and TEMA, with customizable source and length settings.
• Flexible Signal Logic: Generates signals when price breaks above or below the selected MA, with options for confirmation candles and wick or close based breakout detection.
• ATR-Based Filtering: Utilizes ATR to create dynamic breakout bands around the MA, reducing noise and improving breakout validation.
• Breakout Threshold Filtering: Adds an optional minimum percentage price move before a new opposite signal is allowed, preventing rapid reversals.
Why use this indicator?
• Scans up to 40 symbols at the same time.
• Users can define the symbol list, asset class, and automatically detects the symbol separator; warns if any symbols are invalid
• Detected signals are shown directly on the chart as labels, tooltips, or in a compact table.
• The list of signal-generating symbols can be tracked with alerts — no need to watch the chart constantly.
How to Use
███████ Alerts ███████
🔸 Long / Short
To enable Custom Alerts, select the desired alert type (Long or Short) from the indicator's settings under the "Alerts" section, you can customize messages and enable notifications for Long and Short signals. Then, you need to activate the fx alert() function call option in TradingView’s alert creation dialog.
Alert messages include your custom message followed by a list of symbols currently giving signals, each shown on a new line. For example, if your input message is set to “🟢 Long Signal” and BTCUSD and ETHUSD are signaling, the alert will look like this:
🟢 Long Signal
BTCUSD
ETHUSD
This format helps you clearly see the type of signal and each symbol individually, making real-time monitoring easier.
🔸 Alert Delay (seconds)
This setting adds a delay before alerts are triggered. It helps ensure that signals are based on confirmed bar closures for slight timing differences between symbol data feeds (especially in multi-symbol mode). For example, setting a 30-second delay allows all symbols to finish processing before the alert fires, avoiding early or incomplete signal lists.
For best results, try different delay values to see what works best with your selected timeframe.
███████ Display / Signal ███████
🔸 Display Mode
Choose how the indicator presents signals on your chart. Focus on a single symbol (Chart mode), Scan and display multiple symbols at once (Screener mode), or hide visuals and use only tables or alerts (No mode).
• Chart Mode: Displays signals only for the current chart symbol. Useful for testing and optimizing signal conditions before scanning multiple assets.
• Screener Mode: Activates the screener functionality, showing results for all valid symbols in your list. Signals appear as labels on the chart and are also listed in the signal table for easy tracking.
• No (Table Only): Hides all on-chart visuals (labels, markers). Signals are still processed and can be viewed in tables or used with alerts. This mode is ideal when you're using multiple screeners at once and want to avoid overlapping visuals. Each screener can display its results in separate table positions (e.g., bottom right, top left, etc.), so turning off chart visuals helps keep your workspace clean while still tracking multiple symbol groups efficiently. This way, you can also track more than 40 symbols by using multiple screener instances with different symbol groups and table positions.
🔸 Long
You can independently turn ON or OFF the display of Long signals using the toggle.
🔸 Short
You can independently turn ON or OFF the display of Short signals using the toggle.
███████ Symbols ███████
🔸 Symbols
You can enter up to 40 symbols. Symbols must be written in full format. For example: BINANCE:BTCUSDT, NASDAQ:AAPL, or OANDA:EURUSD. TradingView requires this full format to correctly recognize each symbol. Due to TradingView’s limitations, only the first 40 symbols in your list will be processed
- Separator Rules: Letters (A–Z), numbers (0–9), underscore (_), dot (.), and exclamation mark (!) are allowed within symbol names (e.g., BINANCE:BTCUSDT.P). Therefore, avoid using them as separators. Instead, use comma (,) , semicolon (;) , space , or newline to separate multiple symbols.
- Auto Detection: The indicator automatically detects the separator used in your list. If the format is incorrect or a symbol is invalid, a warning will appear to help you fix it.
🔸 Symbol Filter
When scanning multiple symbols, it's important that they belong to the same market type (Crypto, Stocks, Forex, etc.). Different markets have different trading hours, and mixing them may cause issues.
For example, if your chart is using a stock symbol (like NASDAQ:AAPL) and your symbol list includes crypto symbols (like BINANCE:BTCUSDT), the screener may not work correctly. Since stock markets are not open 24/7, the chart time may fall outside of crypto trading hours — causing crypto signals to fail or not update properly.
To avoid this issue, the indicator includes a Symbol Filter. This lets you filter your symbol list to include only the correct asset type (e.g., only Crypto or only Stocks). By using this filter, you make sure the screener runs under the correct market conditions and avoids signal mismatches.
If you set the filter to None , no filtering will be applied. In this case, you are responsible for making sure all listed symbols match your chart’s market type.
For best results, always use symbols from the same market type as your chart symbol. This ensures that candle open/close times align across all symbols, avoiding timing mismatches. Symbols and the chart must follow the same market hours for accurate and consistent signal generation.
🔸 Show Symbols on Table
This feature helps you quickly review the symbols you've entered. When enabled, a table appears in the bottom-right corner of the chart displaying all symbols from your list along with their market types and statuses
- Green background: Symbol is valid and matches the selected Symbol Filter. It can generate signals.
- Gray background: Symbol is valid but does not match the selected filter. It will not generate signals.
- Red background: Symbol is invalid (e.g., due to incorrect names, delisting, or unsupported by broker).
You don’t need to remove invalid or mismatched symbols, but no signals will be generated for them. This visual check makes it easier to catch symbol issues before relying on the screener output.
███████ Signal Display Style ███████
🔸 Display Method
Choose how signals will be shown visually
• Label: The signal appears as a label on the candle. The label includes all triggering symbols as text.
• Tooltip: An icon (such as 🟢 or 🔴) is shown instead of full text. Hold your mouse pointer on the icon on chart for a few seconds to see a tooltip listing the triggered symbols. This method keeps your chart cleaner and less cluttered.
• None: No visual markers appear on candles. Signals are only visible in the signal table — ideal if you're using multiple indicators and want to avoid chart clutter.
🔸 Symbol Display Format
This setting affects the labels, tooltips, signal table, and alert messages, ensuring consistency across all displays. Select whether you want symbols to appear as:
• EXCHANGE:SYMBOL: BINANCE:BTCUSDT
• SYMBOL: BTCUSDT
🔸 Long Signal Icon
Used only in Tooltip mode, these icons (e.g., 🟢 for Long) appear on bars where signals are detected. Customize it freely to match your style or strategy.
🔸 Short Signal Icon
Used only in Tooltip mode, these icons (e.g., 🔴 for Short) appear on bars where signals are detected. Customize it freely to match your style or strategy.
🔸 Size
Adjust the visual size of labels or tooltips. Smaller sizes help reduce clutter when many signals trigger in close proximity.
███████ Signal Table ███████
This section controls the appearance and behavior of the signal table that displays last detected Long and Short signals for your symbols.
🔸 Show
Enable or disable the signal table display on the chart.
🔸 Highlight Signal Duration (Bars)
When a signal occurs, the corresponding cell in the table is highlighted using the selected Long or Short color for this many bars. This helps visually track recent signals over time. The bar where the signal icon appears is counted as 1.
🔸 Table Size
Choose the size of the table to fit your chart layout and readability preferences.
🔸 Table Position
Select where the table appears on your chart (e.g., top right, middle right, bottom left).
🔸 Title
Customize the table header text. The default is “Recent Signals”.
🔸 Background Color
Set the table’s background color and transparency to match your chart’s theme.
🔸 Long Signal Color
Choose the highlight color used to mark Long signals within the table.
🔸 Short Signal Color
Choose the highlight color used to mark Short signals within the table.
🔸 Text Color
Customize the text color inside the table for better contrast and readability.
🔸 Show Bars Since Signal
Optionally display how many bars have passed since each signal appeared. The bar where the signal occurs counts as 1.
███████ Signal ███████
This is the core component of the signal system. You can customize:
🔸 Moving Average Type
Choose from SMA, EMA, WMA, Hull MA, VWMA, RMA, or TEMA
🔸 Length
Adjust the length to suit your strategy.
🔸 Source
Select which price data (e.g., Close, Open, HL2) is used to calculate the MA.
🔸 Confirm Candles
Defines the number of consecutive candles that must break the selected level to confirm a signal.
– If ATR filter is enabled, this level is the ATR bands.
– If ATR is disabled, the Moving Average line is used.
This helps filter out noise and avoid premature signals.
🔸 Break Type
Specifies how the candle must break the level:
– Close: The candle must close beyond the level.
– Wick: A wick touching or exceeding the level is enough.
Both options generate signals only after the candle has closed.
🔸 Filter
This section provides optional filters to improve signal accuracy.
ATR
When the ATR filter is enabled, signals are generated only if the price breaks above the upper ATR line or below the lower ATR line—calculated by adding or subtracting the ATR multiplied threshold from the moving average—and the breakout must occur for the number of consecutive confirmation candles specified by the user input . This helps reduce false signals during low volatility periods.
• Multiplier: Adjusts the width of ATR bands by multiplying the ATR value.
• Length: Sets the period for ATR calculation.
• Smoothing: Selects the smoothing method applied to the ATR (RMA, SMA, EMA, WMA).
Breakout
When enabled, breakout confirmation requires the price to cross above the upper breakout line or below the lower breakout line by a specified percentage from the last signal price.
• Threshold (%): Defines the minimum percentage price movement required to validate a breakout.
• Show Breakout Levels: Toggle to display or hide breakout threshold area on the chart.
PRO Investing - Apex EnginePRO Investing - Apex Engine
1. Core Concept: Why Does This Indicator Exist?
Traditional momentum oscillators like RSI or Stochastic use a fixed "lookback period" (e.g., 14). This creates a fundamental problem: a 14-period setting that works well in a fast, trending market will generate constant false signals in a slow, choppy market, and vice-versa. The market's character is dynamic, but most tools are static.
The Apex Engine was built to solve this problem. Its primary innovation is a self-optimizing core that continuously adapts to changing market conditions. Instead of relying on one fixed setting, it actively tests three different momentum profiles (Fast, Mid, and Slow) in real-time and selects the one that is most synchronized with the current price action.
This is not just a random combination of indicators; it's a deliberate synthesis designed to create a more robust momentum tool. It combines:
Volatility analysis (ATR) to generate adaptive lookback periods.
Momentum measurement (ROC) to gauge the speed of price changes.
Statistical analysis (Correlation) to validate which momentum measurement is most effective right now.
Classic trend filters (Moving Average, ADX) to ensure signals are only taken in favorable market conditions.
The result is an oscillator that aims to be more responsive in volatile trends and more stable in quiet periods, providing a more intelligent and adaptive signal.
2. How It Works: The Engine's Three-Stage Process
To be transparent, it's important to understand the step-by-step logic the indicator follows on every bar. It's a process of Adapt -> Validate -> Signal.
Stage 1: Adapt (Dynamic Length Calculation)
The engine first measures market volatility using the Average True Range (ATR) relative to its own long-term average. This creates a volatility_factor. In high-volatility environments, this factor causes the base calculation lengths to shorten. In low-volatility, they lengthen. This produces three potential Rate of Change (ROC) lengths: dynamic_fast_len, dynamic_mid_len, and dynamic_slow_len.
Stage 2: Validate (Self-Optimizing Mode Selection)
This is the core of the engine. It calculates the ROC for all three dynamic lengths. To determine which is best, it uses the ta.correlation() function to measure how well each ROC's movement has correlated with the actual bar-to-bar price changes over the "Optimization Lookback" period. The ROC length with the highest correlation score is chosen as the most effective profile for the current moment. This "active" mode is reflected in the oscillator's color and the dashboard.
Stage 3: Signal (Normalized Velocity Oscillator)
The winning ROC series is then normalized into a consistent oscillator (the Velocity line) that ranges from -100 (extreme oversold) to +100 (extreme overbought). This ensures signals are comparable across any asset or timeframe. Signals are only generated when this Velocity line crosses its signal line and the trend filters (explained below) give a green light.
3. How to Use the Indicator: A Practical Guide
Reading the Visuals:
Velocity Line (Blue/Yellow/Pink): The main oscillator line. Its color indicates which mode is active (Fast, Mid, or Slow).
Signal Line (White): A moving average of the Velocity line. Crossovers generate potential signals.
Buy/Sell Triangles (▲ / ▼): These are your primary entry signals. They are intentionally strict and only appear when momentum, trend, and price action align.
Background Color (Green/Red/Gray): This is your trend context.
Green: Bullish trend confirmed (e.g., price above a rising 200 EMA and ADX > 20). Only Buy signals (▲) can appear.
Red: Bearish trend confirmed. Only Sell signals (▼) can appear.
Gray: No clear trend. The market is likely choppy or consolidating. No signals will appear; it is best to stay out.
Trading Strategy Example:
Wait for a colored background. A green or red background indicates the market is in a tradable trend.
Look for a signal. For a green background, wait for a lime Buy triangle (▲) to appear.
Confirm the trade. Before entering, confirm the signal aligns with your own analysis (e.g., support/resistance levels, chart patterns).
Manage the trade. Set a stop-loss according to your risk management rules. An exit can be considered on a fixed target, a trailing stop, or when an opposing signal appears.
4. Settings and Customization
This script is open-source, and its settings are transparent. You are encouraged to understand them.
Synaptic Engine Group:
Volatility Period: The master control for the adaptive engine. Higher values are slower and more stable.
Optimization Lookback: How many bars to use for the correlation check.
Switch Sensitivity: A buffer to prevent frantic switching between modes.
Advanced Configuration & Filters Group:
Price Source: The data source for momentum calculation (default close).
Trend Filter MA Type & Length: Define your long-term trend.
Filter by MA Slope: A key feature. If ON, allows for "buy the dip" entries below a rising MA. If OFF, it's stricter, requiring price to be above the MA.
ADX Length & Threshold: Filters out non-trending, choppy markets. Signals will not fire if the ADX is below this threshold.
5. Important Disclaimer
This indicator is a decision-support tool for discretionary traders, not an automated trading system or financial advice. Past performance is not indicative of future results. All trading involves substantial risk. You should always use proper risk management, including setting stop-losses, and never risk more than you are prepared to lose. The signals generated by this script should be used as one component of a broader trading plan.
% / ATR Buy, Target, Stop + Overlay & P/L% / ATR Buy, Target, Stop + Overlay & P/L
This tool combines volatility‑based and fixed‑percentage trade planning into a single, on‑chart overlay—with built‑in profit‑and‑loss estimates. Toggle between ATR or percentage modes, plot your Buy, Target and Stop levels, and see the dollar gain or loss for a specified position size—all in one interactive table and chart display.
NOTE: To activate plotted lines, price labels, P/L rows and table values, enter a Buy Price greater than zero.
What It Does
Mode Toggle: Choose between “ATR” (volatility‑based) or “%” (fixed‑percentage) calculations.
Buy Price Input: Manually enter your entry price.
ATR Mode:
Target = Buy + (ATR × Target Multiplier)
Stop = Buy − (ATR × Stop Multiplier)
Percentage Mode:
Target = Buy × (1 + Target % / 100)
Stop = Buy × (1 – Stop % / 100)
P/L Estimates: Specify a dollar amount to “invest” at your Buy price, and the script calculates:
Gain ($): Profit if Target is hit
Loss ($): Cost if Stop is hit
Visual Overlay: Draws horizontal lines for Buy, Target and Stop, with optional price labels on the chart scale.
Interactive Table: Displays Buy, Target, Stop, ATR/timeframe info (in ATR mode), percentages (in % mode), and P/L rows.
Customization Options
Line Settings:
Choose color, style (solid/dashed/dotted), and width for Buy, Target, Stop lines.
Extend lines rightward only or in both directions.
Table Settings:
Position the table (top/bottom × left/right).
Toggle individual rows: Buy Price; Target (multiplier or %); Stop (multiplier or %); Target ATR %; Stop ATR %; ATR Time Frame; ATR Value; Gain ($); Loss ($).
Customize text colors for each row and background transparency.
General Inputs:
ATR length and optional ATR timeframe override (e.g. use daily ATR on an intraday chart).
Target/Stop multipliers or percentages.
Dollar Amount for P/L calculations.
How to Use It for Trading
Plan Your Entry: Enter your intended Buy Price and position size (dollar amount).
Select Mode: Toggle between ATR or % mode depending on whether you prefer volatility‑based or fixed offsets.
Assess R:R and P/L: Instantly see your Target, Stop levels, and potential profit or loss in dollars.
Visual Reference: Lines and price labels update in real time as you tweak inputs—ideal for live trading, backtesting or trade journaling.
Ideal For
Traders who want both volatility‑based and percentage‑based exit options in one tool
Those who need on‑chart P/L estimates based on position size
Swing and intraday traders focused on objective, rule‑based trade management
Anyone who uses ATR for adaptive stops/targets or fixed percentages for simpler exits
Quantum Reversal Engine [ApexLegion]Quantum Reversal Engine
STRATEGY OVERVIEW
This strategy is constructed using 5 custom analytical filters that analyze different market dimensions - trend structure, momentum expansion, volume confirmation, price action patterns, and reversal detection - with results processed through a multi-component scoring calculation that determines signal generation and position management decisions.
Why These Custom Filters Were Independently Developed:
This strategy employs five custom-developed analytical filters:
1. Apex Momentum Core (AMC) - Custom oscillator with volatility-scaled deviation calculation
Standard oscillators lag momentum shifts by 2-3 bars. Custom calculation designed for momentum analysis
2. Apex Wick Trap (AWT) - Wick dominance analysis for trap detection
Existing wick analysis tools don't quantify trap conditions. Uses specific ratios for wick dominance detection
3. Apex Volume Pulse (AVP) - Volume surge validation with participation confirmation
Volume indicators typically use simple averages. Uses surge multipliers with participation validation
4. Apex TrendGuard (ATG) - Angle-based trend detection with volatility band integration
EMA slope calculations often produce false signals. Uses angle analysis with volatility bands for confirmation
5. Quantum Composite Filter (QCF) - Multi-component scoring and signal generation system
Composite scoring designed to filter noise by requiring multiple confirmations before signal activation.
Each filter represents mathematical calculations designed to address specific analytical requirements.
Framework Operation: The strategy functions as a scoring framework where each filter contributes weighted points based on market conditions. Entry signals are generated when minimum threshold scores are met. Exit management operates through a three-tier system with continued signal strength evaluation determining position holds versus closures at each TP level.
Integration Challenge: The core difficulty was creating a scoring system where five independent filters could work together without generating conflicting signals. This required backtesting to determine effective weight distributions.
Custom Filter Development:
Each of the five filters represents analytical approaches developed through testing and validation:
Integration Validation: Each filter underwent individual testing before integration. The composite scoring system required validation to verify that filters complement rather than conflict with each other, resulting in a cohesive analytical framework that was tested during the development period.
These filters represent custom-developed components created specifically for this strategy, with each component addressing different analytical requirements through testing and parameter adjustment.
Programming Features:
Multi-timeframe data handling with backup systems
Performance optimization techniques
Error handling for live trading scenarios
Parameter adaptation based on market conditions
Strategy Features:
Uses multi-filter confirmation approach
Adapts position holding based on continued signal strength
Includes analysis tools for trade review and optimization
Ongoing Development: The strategy was developed through testing and validation processes during the creation period.
COMPONENT EXPLANATION
EMA System
Uses 8 exponential moving averages (7, 14, 21, 30, 50, 90, 120, 200 periods) for trend identification. Primary signals come from 8/21 EMA crossovers, while longer EMAs provide structural context. EMA 1-4 determine short-term structure, EMA 5-8 provide long-term trend confirmation.
Apex Momentum Core (AMC)
Built custom oscillator mathematics after testing dozens of momentum calculation methods. Final algorithm uses price deviation from EMA baseline with volatility scaling to reduce lag while maintaining accuracy across different market conditions.
Custom momentum oscillator using price deviation from EMA baseline:
apxCI = 100 * (source - emaBase) / (sensitivity * sqrt(deviation + 1))
fastLine = EMA(apxCI, smoothing)
signalLine = SMA(fastLine, 4)
Signals generate when fastLine crosses signalLine at +50/-50 thresholds.
This identifies momentum expansion before traditional oscillators.
Apex Volume Pulse (AVP)
Created volume surge analysis that goes beyond simple averages. Extensive testing determined 1.3x multiplier with participation validation provides reliable confirmation while filtering false volume spikes.
Compares current volume to 21-period moving average.
Requires 1.3x average volume for signal confirmation. This filters out low-volume moves during quiet periods and confirms breakouts with actual participation.
Apex Wick Trap (AWT)
Developed proprietary wick trap detection through analysis of failed breakout patterns. Tested various ratio combinations before settling on 60% wick dominance + 20% body limit as effective trap identification parameters.
Analyzes candle structure to identify failed breakouts:
candleRange = math.max(high - low, 0.00001)
candleBody = math.abs(close - open)
bodyRatio = candleBody / candleRange
upperWick = high - math.max(open, close)
lowerWick = math.min(open, close) - low
upperWickRatio = upperWick / candleRange
lowerWickRatio = lowerWick / candleRange
trapWickLong = showAWT and lowerWickRatio > minWickDom and bodyRatio < bodyToRangeLimit and close > open
trapWickShort = showAWT and upperWickRatio > minWickDom and bodyRatio < bodyToRangeLimit and close < open This catches reversals after fake breakouts.
Apex TrendGuard (ATG)
Built angle-based trend detection after standard EMA crossovers proved insufficient. Combined slope analysis with volatility bands through iterative testing to eliminate false trend signals.
EMA slope analysis with volatility bands:
Fast EMA (21) vs Slow EMA (55) for trend direction
Angle calculation: atan(fast - slow) * 180 / π
ATR bands (1.75x multiplier) for breakout confirmation
Minimum 25° angle for strong trend classification
Core Algorithm Framework
1. Composite Signal Generation
calculateCompositeSignals() =>
// Component Conditions
structSignalLong = trapWickLong
structSignalShort = trapWickShort
momentumLong = amcBuySignal
momentumShort = amcSellSignal
volumeSpike = volume > volAvg_AVP * volMult_AVP
priceStrength_Long = close > open and close > close
priceStrength_Short = close < open and close < close
rsiMfiComboValue = (ta.rsi(close, 14) + ta.mfi(close, 14)) / 2
reversalTrigger_Long = ta.crossover(rsiMfiComboValue, 50)
reversalTrigger_Short = ta.crossunder(rsiMfiComboValue, 50)
isEMACrossUp = ta.crossover(emaFast_ATG, emaSlow_ATG)
isEMACrossDown = ta.crossunder(emaFast_ATG, emaSlow_ATG)
// Enhanced Composite Score Calculation
scoreBuy = 0.0
scoreBuy += structSignalLong ? scoreStruct : 0.0
scoreBuy += momentumLong ? scoreMomentum : 0.0
scoreBuy += flashSignal ? weightFlash : 0.0
scoreBuy += blinkSignal ? weightBlink : 0.0
scoreBuy += volumeSpike_AVP ? scoreVolume : 0.0
scoreBuy += priceStrength_Long ? scorePriceAction : 0.0
scoreBuy += reversalTrigger_Long ? scoreReversal : 0.0
scoreBuy += emaAlignment_Bull ? weightTrendAlign : 0.0
scoreBuy += strongUpTrend ? weightTrendAlign : 0.0
scoreBuy += highRisk_Long ? -1.2 : 0.0
scoreBuy += signalGreenDot ? 1.0 : 0.0
scoreBuy += isAMCUp ? 0.8 : 0.0
scoreBuy += isVssBuy ? 1.5 : 0.0
scoreBuy += isEMACrossUp ? 1.0 : 0.0
scoreBuy += signalRedX ? -1.0 : 0.0
scoreSell = 0.0
scoreSell += structSignalShort ? scoreStruct : 0.0
scoreSell += momentumShort ? scoreMomentum : 0.0
scoreSell += flashSignal ? weightFlash : 0.0
scoreSell += blinkSignal ? weightBlink : 0.0
scoreSell += volumeSpike_AVP ? scoreVolume : 0.0
scoreSell += priceStrength_Short ? scorePriceAction : 0.0
scoreSell += reversalTrigger_Short ? scoreReversal : 0.0
scoreSell += emaAlignment_Bear ? weightTrendAlign : 0.0
scoreSell += strongDownTrend ? weightTrendAlign : 0.0
scoreSell += highRisk_Short ? -1.2 : 0.0
scoreSell += signalRedX ? 1.0 : 0.0
scoreSell += isAMCDown ? 0.8 : 0.0
scoreSell += isVssSell ? 1.5 : 0.0
scoreSell += isEMACrossDown ? 1.0 : 0.0
scoreSell += signalGreenDot ? -1.0 : 0.0
compositeBuySignal = enableComposite and scoreBuy >= thresholdCompositeBuy
compositeSellSignal = enableComposite and scoreSell >= thresholdCompositeSell
if compositeBuySignal and compositeSellSignal
compositeBuySignal := false
compositeSellSignal := false
= calculateCompositeSignals()
// Final Entry Signals
entryCompositeBuySignal = compositeBuySignal and ta.rising(emaFast_ATG, 2)
entryCompositeSellSignal = compositeSellSignal and ta.falling(emaFast_ATG, 2)
Calculates weighted scores from independent modules and activates signals only when threshold requirements are met.
2. Smart Exit Hold Evaluation System
evaluateSmartHold() =>
compositeBuyRecentCount = 0
compositeSellRecentCount = 0
for i = 0 to signalLookbackBars - 1
compositeBuyRecentCount += compositeBuySignal ? 1 : 0
compositeSellRecentCount += compositeSellSignal ? 1 : 0
avgVolume = ta.sma(volume, 20)
volumeSpike = volume > avgVolume * volMultiplier
// MTF Bull/Bear conditions
mtf_bull = mtf_emaFast_final > mtf_emaSlow_final
mtf_bear = mtf_emaFast_final < mtf_emaSlow_final
emaBackupDivergence = math.abs(mtf_emaFast_backup - mtf_emaSlow_backup) / mtf_emaSlow_backup
emaBackupStrong = emaBackupDivergence > 0.008
mtfConflict_Long = inLong and mtf_bear and emaBackupStrong
mtfConflict_Short = inShort and mtf_bull and emaBackupStrong
// Layer 1: ATR-Based Dynamic Threshold (Market Volatility Intelligence)
atr_raw = ta.atr(atrLen)
atrValue = na(atr_raw) ? close * 0.02 : atr_raw
atrRatio = atrValue / close
dynamicThreshold = atrRatio > 0.02 ? 1.0 : (atrRatio > 0.01 ? 1.5 : 2.8)
// Layer 2: ROI-Conditional Time Intelligence (Selective Pressure)
timeMultiplier_Long = realROI >= 0 ? 1.0 : // Profitable positions: No time pressure
holdTimer_Long <= signalLookbackBars ? 1.0 : // Loss positions 1-8 bars: Base
holdTimer_Long <= signalLookbackBars * 2 ? 1.1 : // Loss positions 9-16 bars: +10% stricter
1.3 // Loss positions 17+ bars: +30% stricter
timeMultiplier_Short = realROI >= 0 ? 1.0 : // Profitable positions: No time pressure
holdTimer_Short <= signalLookbackBars ? 1.0 : // Loss positions 1-8 bars: Base
holdTimer_Short <= signalLookbackBars * 2 ? 1.1 : // Loss positions 9-16 bars: +10% stricter
1.3 // Loss positions 17+ bars: +30% stricter
// Dual-Layer Threshold Calculation
baseThreshold_Long = mtfConflict_Long ? dynamicThreshold + 1.0 : dynamicThreshold
baseThreshold_Short = mtfConflict_Short ? dynamicThreshold + 1.0 : dynamicThreshold
timeAdjustedThreshold_Long = baseThreshold_Long * timeMultiplier_Long
timeAdjustedThreshold_Short = baseThreshold_Short * timeMultiplier_Short
// Final Smart Hold Decision with Dual-Layer Intelligence
smartHold_Long = not mtfConflict_Long and smartScoreLong >= timeAdjustedThreshold_Long and compositeBuyRecentCount >= signalMinCount
smartHold_Short = not mtfConflict_Short and smartScoreShort >= timeAdjustedThreshold_Short and compositeSellRecentCount >= signalMinCount
= evaluateSmartHold()
Evaluates whether to hold positions past TP1/TP2/TP3 levels based on continued signal strength, volume confirmation, and multi-timeframe trend alignment
HOW TO USE THE STRATEGY
Step 1: Initial Setup
Apply strategy to your preferred timeframe (backtested on 15M)
Enable "Use Heikin-Ashi Base" for smoother signals in volatile markets
"Show EMA Lines" and "Show Ichimoku Cloud" are enabled for visual context
Set default quantities to match your risk management (5% equity default)
Step 2: Signal Recognition
Visual Signal Guide:
Visual Signal Guide - Complete Reference:
🔶 Red Diamond: Bearish momentum breakdown - short reversal signal
🔷 Blue Diamond: Strong bullish momentum - long reversal signal
🔵 Blue Dot: Volume-confirmed directional move - trend continuation
🟢 Green Dot: Bullish EMA crossover - trend reversal confirmation
🟠 Orange X: Oversold reversal setup - counter-trend opportunity
❌ Red X: Bearish EMA breakdown - trend reversal warning
✡ Star Uprising: Strong bullish convergence
💥 Ultra Entry: Ultra-rapid downward momentum acceleration
▲ VSS Long: Velocity-based bullish momentum confirmation
▼ VSS Short: Velocity-based bearish momentum confirmation
Step 3: Entry Execution
For Long Positions:
1. ✅ EMA1 crossed above EMA2 exactly 3 bars ago [ta.crossover(ema1,ema2) ]
2. ✅ Current EMA structure: EMA1 > EMA2 (maintained)
3. ✅ Composite score ≥ 5.0 points (6.5+ for 5-minute timeframes)
4. ✅ Cooldown period completed (no recent stop losses)
5. ✅ Volume spike confirmation (green dot/blue dot signals)
6. ✅ Bullish candle closes above EMA structure
For Short Positions:
1. ✅ EMA1 crossed below EMA2 exactly 3 bars ago [ta.crossunder(ema1,ema2) ]
2. ✅ Current EMA structure: EMA1 < EMA2 (maintained)
3. ✅ Composite score ≥ 5.4 points (7.0+ for 5-minute timeframes)
4. ✅ Cooldown period completed (no recent stop losses)
5. ✅ Momentum breakdown (red diamond/red X signals)
6. ✅ Bearish candle closes below EMA structure
🎯 Critical Timing Note: The strategy requires EMA crossover to have occurred 3 bars prior to entry, not at the current bar. This attempts to avoid premature entries and may improve signal reliability.
Step 4: Reading Market Context
EMA Ribbon Interpretation:
All EMAs ascending = Strong uptrend context
EMAs 1-3 above EMAs 4-8 = Bullish structure
Tight EMA spacing = Low volatility/consolidation
Wide EMA spacing = High volatility/trending
Ichimoku Cloud Context:
Price above cloud = Bullish environment
Price below cloud = Bearish environment
Cloud color intensity = Momentum strength
Thick cloud = Strong support/resistance
THE SMART EXIT GRID SYSTEM
Smart Exit Grid Approach:
The Smart Exit Grid uses dynamic hold evaluation that continuously analyzes market conditions after position entry. This differs from traditional fixed profit targets by adapting exit timing based on real-time signal strength.
How Smart Exit Grid System Works
The system operates through three evaluation phases:
Smart Score Calculation:
The smart score calculation aggregates 22 signal components in real-time, combining reversal warnings, continuation signals, trend alignment indicators, EMA structural analysis, and risk penalties into a numerical representation of market conditions. MTF analysis provides additional confirmation as a separate validation layer.
Signal Stack Management:
The per-tick signal accumulation system monitors 22 active signal types with MTF providing trend validation and conflict detection as a separate confirmation layer.
Take Profit Progression:
Smart Exit Activation:
The QRE system activates Smart Exit Grid immediately upon position entry. When strategy.entry() executes, the system initializes monitoring systems designed to track position progress.
Upon position opening, holdTimer begins counting, establishing the foundation for subsequent decisions. The Smart Exit Grid starts accumulating signals from entry, with all 22 signal components beginning real-time tracking when the trade opens.
The system operates on continuous evaluation where smartScoreLong and smartScoreShort calculate from the first tick after entry. QRE's approach is designed to capture market structure changes, trend deteriorations, or signal pattern shifts that can trigger protective exits even before the first take profit level is reached.
This activation creates a proactive position management framework. The 8-candle sliding window starts from entry, meaning that if market conditions change rapidly after entry - due to news events, liquidity shifts, or technical changes - the system can respond within the configured lookback period.
TP Markers as Reference Points:
The TP1, TP2, and TP3 levels function as reference points rather than mandatory exit triggers. When longTP1Hit or shortTP1Hit conditions activate, they serve as profit confirmation markers that inform the Smart Exit algorithm about achieved reward levels, but don't automatically initiate position closure.
These TP markers enhance the Smart Exit decision matrix by providing profit context to ongoing signal evaluation. The system recognizes when positions have achieved target returns, but the actual exit decision remains governed by continuous smart score evaluation and signal stack analysis.
TP2 Reached: Enhanced Monitoring
TP2 represents significant profit capture with additional monitoring features:
This approach is designed to help avoid premature profit-taking during trending conditions. If TP2 is reached but smartScoreLong remains above the dynamic threshold and the 8-candle sliding window shows persistent signals, the position continues holding. If market structure deteriorates before reaching TP2, the Smart Exit can trigger closure based on signal analysis.
The visual TP circles that appear when levels are reached serve as performance tracking tools, allowing users to see how frequently entries achieve various profit levels while understanding that actual exit timing depends on market structure analysis.
Risk Management Systems:
Operating independently from the Smart Exit Grid are two risk management systems: the Trap Wick Detection Protocol and the Stop Loss Mechanism. These systems maintain override authority over other exit logic.
The Trap Wick System monitors for conditionBearTrapExit during long positions and conditionBullTrapExit during short positions. When detected, these conditions trigger position closure with state reset, bypassing Smart Exit evaluations. This system recognizes that certain candlestick patterns may indicate reversal risk.
Volatility Exit Monitoring: The strategy monitors for isStrongBearCandle combined with conditionBearTrapExit, recognizing when market structure may be shifting.
Volume Validation: Before exiting on volatility, the strategy requires volume confirmation: volume > ta.sma(volume, 20) * 1.8. This is designed to filter exits on weak, low-volume movements.
The Stop Loss Mechanism operates through multiple triggers including traditional price-based stops (longSLHit, shortSLHit) and early exit conditions based on smart score deterioration combined with negative ROI. The early exit logic activates when smartScoreLong < 1.0 or smartScoreShort < 1.0 while realROI < -0.9%.
These risk management systems are designed so that risk scenarios can trigger protective closure with state reset across all 22 signal counters, TP tracking variables, and smart exit states.
This architecture - Smart Exit activation, TP markers as navigation tools, and independent risk management - creates a position management system that adapts to market conditions while maintaining risk discipline through dedicated protection protocols.
TP3 Reached: Enhanced Protection
Once TP3 is hit, the strategy shifts into enhanced monitoring:
EMA Structure Monitoring: isEMAStructureDown becomes a primary exit trigger
MTF Alignment: The higher timeframe receives increased consideration
Wick Trap Priority: conditionBearTrapExit becomes an immediate exit signal
Approach Differences:
Traditional Fixed Exits:
Exit at predetermined levels regardless of market conditions
May exit during trend continuation
May exit before trend completion
Limited adaptation to changing volatility
Smart Exit Grid Approach:
Adaptive timing based on signal conditions
Exits when supporting signals weaken
Multi-timeframe validation for trend confirmation
Volume confirmation requirements for holds
Structural monitoring for trend analysis
Dynamic ATR-Based Smart Score Threshold System
Market Volatility Adaptive Scoring
// Real-time ATR Analysis
atr_raw = ta.atr(atrLen)
atrValue = na(atr_raw) ? close * 0.02 : atr_raw
atrRatio = atrValue / close
// Three-Tier Dynamic Threshold Matrix
dynamicThreshold = atrRatio > 0.02 ? 1.0 : // High volatility: Lower threshold
(atrRatio > 0.01 ? 1.5 : // Medium volatility: Standard
2.8) // Low volatility: Higher threshold
The market volatility adaptive scoring calculates real-time ATR with a 2% fallback for new markets. The atrRatio represents the relationship between current volatility and price, creating a foundation for threshold adjustment.
The three-tier dynamic threshold matrix responds to market conditions by adjusting requirements based on volatility levels: lowering thresholds during high volatility periods above 2% ATR ratio to 1.0 points, maintaining standard requirements at 1.5 points for medium volatility between 1-2%, and raising standards to 2.8 points during low volatility periods below 1%.
Profit-Loss Adaptive Management:
The system applies different evaluation criteria based on position performance:
Winning Positions (realROI ≥ 0%):
→ timeMultiplier = 1.0 (No additional pressure)
→ Maintains base threshold requirements
→ Allows natural progression to TP2/TP3 levels
Losing Positions (realROI < 0%):
→ Progressive time pressure activated
→ Increasingly strict requirements over time
→ Faster decision-making on underperforming trades
ROI-Adaptive Smart Hold Decision Process:
The strategy uses a profit-loss adaptive system:
Winning Position Management (ROI ≥ 0%):
✅ Standard threshold requirements maintained
✅ No additional time-based pressure applied
✅ Allows positions to progress toward TP2/TP3 levels
✅ timeMultiplier remains at 1.0 regardless of hold duration
Losing Position Management (ROI < 0%):
⚠️ Time-based threshold adjustments activated
⚠️ Progressive increase in required signal strength over time
⚠️ Earlier exit evaluation on underperforming positions
⚠️ timeMultiplier increases from 1.0 → 1.1 → 1.3 based on hold duration
Real-Time Monitoring:
Monitor Analysis Table → "Smart" filter → "Score" vs "Dynamic Threshold"
Winning positions: Evaluation based on signal strength deterioration only
Losing positions: Evaluation considers both signal strength and progressive time adjustments
Breakeven positions (0% ROI): Treated as winning positions - no time adjustments
This approach differentiates between winning and losing positions in the hold evaluation process, requiring higher signal thresholds for extended holding of losing positions while maintaining standard requirements for winning ones.
ROI-Conditional Decision Matrix Examples:
Scenario 1 - Winning Position in Any Market:
Position ROI: +0.8% → timeMultiplier = 1.0 (regardless of hold time)
ATR Medium (1.2%) → dynamicThreshold = 1.5
Final Threshold = 1.5 × 1.0 = 1.5 points ✅ Position continues
Scenario 2 - Losing Position, Extended Hold:
Position ROI: -0.5% → Time pressure activated
Hold Time: 20 bars → timeMultiplier = 1.3
ATR Low (0.8%) → dynamicThreshold = 2.8
Final Threshold = 2.8 × 1.3 = 3.64 points ⚡ Enhanced requirements
Scenario 3 - Fresh Losing Position:
Position ROI: -0.3% → Time pressure activated
Hold Time: 5 bars → timeMultiplier = 1.0 (still early)
ATR High (2.1%) → dynamicThreshold = 1.0
Final Threshold = 1.0 × 1.0 = 1.0 points 📊 Recovery opportunity
Scenario 4 - Breakeven Position:
Position ROI: 0.0% → timeMultiplier = 1.0 (no pressure)
Hold Time: 15 bars → No time penalty applied
Final Threshold = dynamicThreshold only ⚖️ Neutral treatment
🔄8-Candle Sliding Window Signal Rotation System
Composite Signal Counting Mechanism
// Dynamic Lookback Window (configurable: default 8)
signalLookbackBars = input.int(8, "Composite Lookback Bars", minval=1, maxval=50)
// Rolling Signal Analysis
compositeBuyRecentCount = 0
compositeSellRecentCount = 0
for i = 0 to signalLookbackBars - 1
compositeBuyRecentCount += compositeBuySignal ? 1 : 0
compositeSellRecentCount += compositeSellSignal ? 1 : 0
Candle Flow Example (8-bar window):
→
✓ ✓ ✗ ✓ ✗ ✓ ✗ ✓ 🗑️
New Signal Count = 5/8 signals in window
Threshold Check: 5 ≥ signalMinCount (2) = HOLD CONFIRMED
Signal Decay & Refresh Mechanism
// Signal Persistence Tracking
if compositeBuyRecentCount >= signalMinCount
smartHold_Long = true
else
smartHold_Long = false
The composite signal counting operates through a configurable sliding window. The system maintains rolling counters that scan backward through the specified number of candles.
During each evaluation cycle, the algorithm iterates through historical bars, incrementing counters when composite signals are detected. This creates a dynamic signal persistence measurement where recent signal density determines holding decisions.
The sliding window rotation functions like a moving conveyor belt where new signals enter while the oldest signals drop off. For example, in an 8-bar window, if 5 out of 8 recent candles showed composite buy signals, and the minimum required count is 2, the system confirms the hold condition. As new bars form, the window slides forward, potentially changing the signal count and triggering exit conditions when signal density falls below the threshold.
Signal decay and refresh occur continuously where smartHold_Long remains true only when compositeBuyRecentCount exceeds signalMinCount. When recent signal density drops below the minimum requirement, the system switches to exit mode.
Advanced Signal Stack Management - 22-Signal Real-Time Evaluation
// Long Position Signal Stacking (calc_on_every_tick=true)
if inLong
// Primary Reversal Signals
if signalRedDiamond: signalCountRedDiamond += 1 // -0.5 points
if signalStarUprising: signalCountStarUprising += 1 // +1.5 points
if entryUltraShort: signalCountUltra += 1 // -1.0 points
// Trend Confirmation Signals
if strongUpTrend: trendUpCount_Long += 1 // +1.5 points
if emaAlignment_Bull: bullAlignCount_Long += 1 // +1.0 points
// Risk Assessment Signals
if highRisk_Long: riskCount_Long += 1 // -1.5 points
if topZone: tzoneCount_Long += 1 // -0.5 points
The per-tick signal accumulation system operates with calc_on_every_tick=true for real-time responsiveness. During long positions, the system monitors primary reversal signals where Red Diamond signals subtract 0.5 points as reversal warnings, Star Uprising adds 1.5 points for continuation signals, and Ultra Short signals deduct 1.0 points as counter-trend warnings.
Trend confirmation signals provide weighted scoring where strongUpTrend adds 1.5 points for aligned momentum, emaAlignment_Bull contributes 1.0 point for structural support, and various EMA-based confirmations contribute to the overall score. Risk assessment signals apply negative weighting where highRisk_Long situations subtract 1.5 points, topZone conditions deduct 0.5 points, and other risk factors create defensive scoring adjustments.
The smart score calculation aggregates all 22 components in real-time, combining reversal warnings, continuation signals, trend alignment indicators, EMA structural analysis, and risk penalties into a numerical representation of market conditions. This score updates continuously, providing the foundation for hold-or-exit decisions.
MULTI-TIMEFRAME (MTF) SYSTEM
MTF Data Collection
The strategy requests higher timeframe data (default 30-minute) for trend confirmation:
= request.security(syminfo.tickerid, mtfTimeframe, , lookahead=barmerge.lookahead_off, gaps=barmerge.gaps_off)
MTF Watchtower System - Implementation Logic
The system employs a timeframe discrimination protocol where currentTFInMinutes is compared against a 30-minute threshold. This creates different operational behavior between timeframes:
📊 Timeframe Testing Results:
30M+ charts: Full MTF confirmation → Tested with full features
15M charts: Local EMA + adjusted parameters → Standard testing baseline
5M charts: Local EMA only → Requires parameter adjustment
1M charts: High noise → Limited testing conducted
When the chart timeframe is 30 minutes or above, the strategy activates useMTF = true and requests external MTF data through request.security(). For timeframes below 30 minutes, including your 5-minute setup, the system deliberately uses local EMA calculations to avoid MTF lag and data inconsistencies.
The triple-layer data sourcing architecture works as follows: timeframes from 1 minute to 29 minutes rely on chart-based EMA calculations for immediate responsiveness. Timeframes of 30 minutes and above utilize MTF data through the security function, with a backup system that doubles the EMA length (emaLen * 2) if MTF data fails. When MTF data is unavailable or invalid, the system falls back to local EMA as the final safety net.
Data validation occurs through a pipeline where mtf_dataValid checks not only for non-null values but also verifies that EMA values are positive above zero. The system tracks data sources through mtf_dataSource which displays "MTF Data" for successful external requests, "Backup EMA" for failed MTF with backup system active, or "Chart EMA" for local calculations.
🔄 MTF Smart Score Caching & Recheck System
// Cache Update Decision Logic
mtfSmartIntervalSec = input.int(300, "Smart Grid Recheck Interval (sec)") // 5-minute cache
canRecheckSmartScore = na(timenow) ? false :
(na(lastCheckTime) or (timenow - lastCheckTime) > mtfSmartIntervalSec * 1000)
// Cache Management
if canRecheckSmartScore
lastCheckTime := timenow
cachedSmartScoreLong := smartScoreLong // Store current calculation
cachedSmartScoreShort := smartScoreShort
The performance-optimized caching system addresses the computational intensity of continuous MTF analysis through intelligent interval management. The mtfSmartIntervalSec parameter, defaulting to 300 seconds (5 minutes), determines cache refresh frequency. The system evaluates canRecheckSmartScore by comparing current time against lastCheckTime plus the configured interval.
When cache updates trigger, the system stores current calculations in cachedSmartScoreLong and cachedSmartScoreShort, creating stable reference points that reduce excessive MTF requests. This cache management balances computational efficiency with analytical accuracy.
The cache versus real-time hybrid system creates a multi-layered decision matrix where immediate signals update every tick for responsive market reaction, cached MTF scores refresh every 5 minutes for stability filtering, dynamic thresholds recalculate every bar for volatility adaptation, and sliding window analysis updates every bar for trend persistence validation.
This architecture balances real-time signal detection with multi-timeframe strategic validation, creating adaptive trading intelligence that responds immediately to market changes while maintaining strategic stability through cached analysis and volatility-adjusted decision thresholds.
⚡The Execution Section Deep Dive
The execution section represents the culmination of all previous systems – where analysis transforms into action.
🚪 Entry Execution: The Gateway Protocol
Primary Entry Validation:
Entry isn't just about seeing a signal – it's about passing through multiple security checkpoints, each designed to filter out low-quality opportunities.
Stage 1: Signal Confirmation
entryCompositeBuySignal must be TRUE for longs
entryCompositeSellSignal must be TRUE for shorts
Stage 2: Enhanced Entry Validation
The strategy employs an "OR" logic system that recognizes different types of market opportunities:
Path A - Trend Reversal Entry:
When emaTrendReversal_Long triggers, it indicates the market structure is shifting in favor of the trade direction. This isn't just about a single EMA crossing – it represents a change in market momentum that experienced traders recognize as potential high-probability setups.
Path B - Momentum Breakout Entry:
The strongBullMomentum condition is where QRE identifies accelerating market conditions:
Criteria:
EMA1 rising for 3+ candles AND
EMA2 rising for 2+ candles AND
Close > 10-period high
This combination captures those explosive moves where the market doesn't just trend – it accelerates, creating momentum-driven opportunities.
Path C - Recovery Entry:
When previous exit states are clean (no recent stop losses), the strategy permits entry based purely on signal strength. This pathway is designed to help avoid the strategy becoming overly cautious after successful trades.
🛡️ The Priority Exit Matrix: When Rules Collide
Not all exit signals are created equal. QRE uses a strict hierarchy that is designed to avoid conflicting signals from causing hesitation:
Priority Level 1 - Exception Exits (Immediate Action):
Condition: TP3 reached AND Wick Trap detected
Action: Immediate exit regardless of other signals
Rationale: Historical analysis suggests wick traps at TP3 may indicate potential reversals
Priority Level 2 - Structural Breakdown:
Condition: TP3 active AND EMA structure deteriorating AND Smart Score insufficient
Logic: isEMAStructureDown AND NOT smartHold_Long
This represents the strategy recognizing that the underlying market structure that justified the trade is failing. It's like a building inspector identifying structural issues – you don't wait for additional confirmation.
Priority Level 3 - Enhanced Volatility Exits:
Conditions: TP2 active AND Strong counter-candle AND Wick trap AND Volume spike
Logic: Multiple confirmation required to reduce false exits
Priority Level 4 - Standard Smart Score Exits:
Condition: Any TP level active AND smartHold evaluates to FALSE
This is the bread-and-butter exit logic where signal deterioration triggers exit
⚖️ Stop Loss Management: Risk Control Protocol
Dual Stop Loss System:
QRE provides two stop loss modes that users can select based on their preference:
Fixed Mode (Default - useAdaptiveSL = false):
Uses predetermined percentage levels regardless of market volatility:
- Long SL = entryPrice × (1 - fixedRiskP - slipBuffer)
- Short SL = entryPrice × (1 + fixedRiskP + slipBuffer)
- Default: 0.6% risk + 0.3% slippage buffer = 0.9% total stop
- Consistent and predictable stop loss levels
- Recommended for users who prefer stable risk parameters
Adaptive Mode (Optional - useAdaptiveSL = true):
Dynamic system that adjusts stop loss based on market volatility:
- Base Calculation uses ATR (Average True Range)
- Long SL = entryPrice × (1 - (ATR × atrMultSL) / entryPrice - slipBuffer)
- Short SL = entryPrice × (1 + (ATR × atrMultSL) / entryPrice + slipBuffer)
- Automatically widens stops during high volatility periods
- Tightens stops during low volatility periods
- Advanced users can enable for volatility-adaptive risk management
Trend Multiplier Enhancement (Both Modes):
When strongUpTrend is detected for long positions, the stop loss receives 1.5x breathing room. Strong trends often have deeper retracements before continuing. This is designed to help avoid the strategy being shaken out of active trades by normal market noise.
Mode Selection Guidance:
- New Users: Start with Fixed Mode for predictable risk levels
- Experienced Users: Consider Adaptive Mode for volatility-responsive stops
- Volatile Markets: Adaptive Mode may provide better stop placement
- Stable Markets: Fixed Mode often sufficient for consistent risk management
Early Exit Conditions:
Beyond traditional stop losses, QRE implements "smart stops" that trigger before price-based stops:
Early Long Exit: (smartScoreLong < 1.0 OR prev5BearCandles) AND realROI < -0.9%
🔄 State Management: The Memory System
Complete State Reset Protocol:
When a position closes, QRE doesn't just wipe the slate clean – it performs a methodical reset:
TP State Cleanup:
All Boolean flags: tp1/tp2/tp3HitBefore → FALSE
All Reached flags: tp1/tp2/tp3Reached → FALSE
All Active flags: tp1/tp2/tp3HoldActive → FALSE
Signal Counter Reset:
Every one of the 22 signal counters returns to zero.
This is designed to avoid signal "ghosting" where old signals influence new trades.
Memory Preservation:
While operational states reset, certain information is preserved for learning:
killReasonLong/Short: Why did this trade end?
lastExitWasTP1/TP2/TP3: What was the exit quality?
reEntryCount: How many consecutive re-entries have occurred?
🔄 Re-Entry Logic: The Comeback System
Re-Entry Conditions Matrix:
QRE implements a re-entry system that recognizes not all exits are created equal:
TP-Based Re-Entry (Enabled):
Criteria: Previous exit was TP1, TP2, or TP3
Cooldown: Minimal or bypassed entirely
Logic: Target-based exits indicate potentially viable market conditions
EMA-Based Re-Entry (Conditional):
Criteria: Previous exit was EMA-based (structural change)
Requirements: Must wait for EMA confirmation in new direction
Minimum Wait: 5 candles
Advanced Re-Entry Features:
When adjustReEntryTargets is enabled, the strategy becomes more aggressive with re-entries:
Target Adjustment: TP1 multiplied by reEntryTP1Mult (default 2.0)
Stop Adjustment: SL multiplied by reEntrySLMult (default 1.5)
Logic: If we're confident enough to re-enter, we should be confident enough to hold for bigger moves
Performance Tracking: Strategy tracks re-entry win rate, average ROI, and total performance separately from initial entries for optimization analysis.
📊 Exit Reason Analytics: Learning from Every Trade
Kill Reason Tracking:
Every exit is categorized and stored:
"TP3 Exit–Wick Trap": Exit at target level with wick pattern detection
"Smart Exit–EMA Down": Structural breakdown exit
"Smart Exit–Volatility": Volatility-based protection exit
"Exit Post-TP1/TP2/TP3": Standard smart exit progression
"Long SL Exit" / "Short SL Exit": Stop loss exits
Performance Differentiation:
The strategy tracks performance by exit type, allowing for continuous analysis:
TP-based exits: Achieved target levels, analyze for pattern improvement
EMA-based exits: Mixed results, analyze for pattern improvement
SL-based exits: Learning opportunities, adjust entry criteria
Volatility exits: Protective measures, monitor performance
🎛️ Trailing Stop Implementation:
Conditional Trailing Activation:
Activation Criteria: Position profitable beyond trailingStartPct AND
(TP hold active OR re-entry trade)
Dynamic Trailing Logic:
Unlike simple trailing stops, QRE's implementation considers market context:
Trending Markets: Wider trail offsets to avoid whipsaws
Volatile Markets: Tighter offsets to protect gains
Re-Entry Trades: Enhanced trailing to maximize second-chance opportunities
Return-to-Entry Protection:
When deactivateOnReturn is enabled, the strategy will close positions that return to entry level after being profitable. This is designed to help avoid the frustration of watching profitable trades turn into losers.
🧠 How It All Works Together
The beauty of QRE lies not in any single component, but in how everything integrates:
The Entry Decision: Multiple pathways are designed to help identify opportunities while maintaining filtering standards.
The Progression System: Each TP level unlocks new protection features, like achieving ranks in a video game.
The Exit Matrix: Prioritized decision-making aims to reduce analysis paralysis while providing appropriate responses to different market conditions.
The Memory System: Learning from each trade while preventing contamination between separate opportunities.
The Re-Entry Logic: Re-entry system that balances opportunity with risk management.
This creates a trading system where entry conditions filter for quality, progression systems adapt to changing market conditions, exit priorities handle conflicting signals intelligently, memory systems learn from each trade cycle, and re-entry logic maximizes opportunities while managing risk exposure.
📊 ANALYSIS TABLE INTERPRETATION -
⚙️ Enabling Analysis Mode
Navigate to strategy settings → "Testing & Analysis" → Enable "Show Analysis Table". The Analysis Table displays different information based on the selected test filter and provides real-time insight into all strategy components, helping users understand current market conditions, position status, and system decision-making processes.
📋 Filter Mode Interpretations
"All" Mode (Default View):
Composite Section:
Buy Score: Aggregated strength from all 22 bullish signals (threshold 5.0+ triggers entry consideration)
Sell Score: Aggregated strength from all 22 bearish signals (threshold 5.4+ triggers entry consideration)
APEX Filters:
ATG Trend: Shows current trend direction analysis
Indicates whether momentum filters are aligned for directional bias
ReEntry Section:
Most Recent Exit: Displays exit type and timeframe since last position closure
Status: Shows if ReEntry system is Ready/Waiting/Disabled
Count: Current re-entry attempts versus maximum allowed attempts
Position Section (When Active):
Status: Current position state (LONG/SHORT/FLAT)
ROI: Dual calculation showing Custom vs Real ROI percentages
Entry Price: Original position entry level
Current Price: Live market price for comparison
TP Tracking: Progress toward profit targets
"Smart" Filter (Critical for Active Positions):
Smart Exit Section:
Hold Timer: Time elapsed since position opened (bar-based counting)
Status: Whether Smart Exit Grid is Enabled/Disabled
Score: Current smart score calculation from 22-component matrix
Dynamic Threshold: ATR-based minimum score required for holding
Final Threshold: Time and ROI-adjusted threshold actually used for decisions
Score Check: Pass/Fail based on Score vs Final Threshold comparison
Smart Hold: Current hold decision status
Final Hold: Final recommendation based on all factors
🎯 Advanced Smart Exit Debugging - ROI & Time-Based Threshold System
Understanding the Multi-Layer Threshold System:
Layer 1: Dynamic Threshold (ATR-Based)
atrRatio = ATR / close
dynamicThreshold = atrRatio > 0.02 ? 1.0 : // High volatility: Lower threshold
(atrRatio > 0.01 ? 1.5 : // Medium volatility: Standard
2.8) // Low volatility: Higher threshold
Layer 2: Time Multiplier (ROI & Duration-Based)
Winning Positions (ROI ≥ 0%):
→ timeMultiplier = 1.0 (No time pressure, regardless of hold duration)
Losing Positions (ROI < 0%):
→ holdTimer ≤ 8 bars: timeMultiplier = 1.0 (Early stage, standard requirements)
→ holdTimer 9-16 bars: timeMultiplier = 1.1 (10% stricter requirements)
→ holdTimer 17+ bars: timeMultiplier = 1.3 (30% stricter requirements)
Layer 3: Final Threshold Calculation
finalThreshold = dynamicThreshold × timeMultiplier
Examples:
- Winning Position: 2.8 × 1.0 = 2.8 (Always standard)
- Losing Position (Early): 2.8 × 1.0 = 2.8 (Same as winning initially)
- Losing Position (Extended): 2.8 × 1.3 = 3.64 (Much stricter)
Real-Time Debugging Display:
Smart Exit Section shows:
Score: 3.5 → Current smartScoreLong/Short value
Dynamic Threshold: 2.8 → Base ATR-calculated threshold
Final Threshold: 3.64 (ATR×1.3) → Actual threshold used for decisions
Score Check: FAIL (3.5 vs 3.64) → Pass/Fail based on final comparison
Final Hold: NO HOLD → Actual system decision
Position Status Indicators:
Winner + Early: ATR×1.0 (No pressure)
Winner + Extended: ATR×1.0 (No pressure - winners can run indefinitely)
Loser + Early: ATR×1.0 (Recovery opportunity)
Loser + Extended: ATR×1.1 or ATR×1.3 (Increasing pressure to exit)
MTF Section:
Data Source: Shows whether using MTF Data/EMA Backup/Local EMA
Timeframe: Configured watchtower timeframe setting
Data Valid: Confirms successful MTF data retrieval status
Trend Signal: Higher timeframe directional bias analysis
Close Price: MTF price data availability confirmation
"Composite" Filter:
Composite Section:
Buy Score: Real-time weighted scoring from multiple indicators
Sell Score: Opposing directional signal strength
Threshold: Minimum scores required for signal activation
Components:
Flash/Blink: Momentum acceleration indicators (F = Flash active, B = Blink active)
Individual filter contributions showing which specific signals are firing
"ReEntry" Filter:
ReEntry System:
System: Shows if re-entry feature is Enabled/Disabled
Eligibility: Conditions for new entries in each direction
Performance: Success metrics of re-entry attempts when enabled
🎯 Key Status Indicators
Status Column Symbols:
✓ = Condition met / System active / Signal valid
✗ = Condition not met / System inactive / No signal
⏳ = Cooldown active (waiting period)
✅ = Ready state / Good condition
🔄 = Processing / Transitioning state
🔍 Critical Reading Guidelines
For Active Positions - Smart Exit Priority Reading:
1. First Check Position Type:
ROI ≥ 0% = Winning Position (Standard requirements)
ROI < 0% = Losing Position (Progressive requirements)
2. Check Hold Duration:
Early Stage (≤8 bars): Standard multiplier regardless of ROI
Extended Stage (9-16 bars): Slight pressure on losing positions
Long Stage (17+ bars): Strong pressure on losing positions
3. Score vs Final Threshold Analysis:
Score ≥ Final Threshold = HOLD (Continue position)
Score < Final Threshold = EXIT (Close position)
Watch for timeMultiplier changes as position duration increases
4. Understanding "Why No Hold?"
Common scenarios when Score Check shows FAIL:
Losing position held too long (timeMultiplier increased to 1.1 or 1.3)
Low volatility period (dynamic threshold raised to 2.8)
Signal deterioration (smart score dropped below required level)
MTF conflict (higher timeframe opposing position direction)
For Entry Signal Analysis:
Composite Score Reading: Signal strength relative to threshold requirements
Component Analysis: Individual filter contributions to overall score
EMA Structure: Confirm 3-bar crossover requirement met
Cooldown Status: Ensure sufficient time passed since last exit
For ReEntry Opportunities (when enabled):
System Status: Availability and eligibility for re-engagement
Exit Type Analysis: TP-based exits enable immediate re-entry, SL-based exits require cooldown
Condition Monitoring: Requirements for potential re-entry signals
Debugging Common Issues:
Issue: "Score is high but no hold?"
→ Check Final Threshold vs Score (not Dynamic Threshold)
→ Losing position may have increased timeMultiplier
→ Extended hold duration applying pressure
Issue: "Why different thresholds for same score?"
→ Position ROI status affects multiplier
→ Time elapsed since entry affects multiplier
→ Market volatility affects base threshold
Issue: "MTF conflicts with local signals?"
→ Higher timeframe trend opposing position
→ System designed to exit on MTF conflicts
→ Check MTF Data Valid status
⚡ Performance Optimization Notes
For Better Performance:
Analysis table updates may impact performance on some devices
Use specific filters rather than "All" mode for focused monitoring
Consider disabling during live trading for optimal chart performance
Enable only when needed for debugging or analysis
Strategic Usage:
Monitor "Smart" filter when positions are active for exit timing decisions
Use "Composite" filter during setup phases for signal strength analysis
Reference "ReEntry" filter after position closures for re-engagement opportunities
Track Final Threshold changes to understand exit pressure evolution
Advanced Debugging Workflow:
Position Entry Analysis:
Check Composite score vs threshold
Verify EMA crossover timing (3 bars prior)
Confirm cooldown completion
Hold Decision Monitoring:
Track Score vs Final Threshold progression
Monitor timeMultiplier changes over time
Watch for MTF conflicts
Exit Timing Analysis:
Identify which threshold layer caused exit
Track performance by exit type
Analyze re-entry eligibility
This analysis system provides transparency into strategy decision-making processes, allowing users to understand how signals are generated and positions are managed according to the programmed logic during various market conditions and position states.
SIGNAL TYPES AND CHARACTERISTICS
🔥 Core Momentum Signals
Flash Signal
Calculation: ta.rma(math.abs(close - close ), 5) > ta.sma(math.abs(close - close ), 7)
Purpose: Detects sudden price acceleration using smoothed momentum comparison
Characteristics: Triggers when recent price movement exceeds historical average movement
Usage: Primary momentum confirmation across multiple composite calculations
Weight: 1.3 points in composite scoring
Blink Signal
Calculation: math.abs(ta.change(close, 1)) > ta.sma(math.abs(ta.change(close, 1)), 5)
Purpose: Identifies immediate price velocity spikes
Characteristics: More sensitive than Flash, captures single-bar momentum bursts
Usage: Secondary momentum confirmation, often paired with Flash
Weight: 1.3 points in composite scoring
⚡ Advanced Composite Signals
Apex Pulse Signal
Calculation: apexAngleValue > 30 or apexAngleValue < -30
Purpose: Detects extreme EMA angle momentum
Characteristics: Identifies when trend angle exceeds ±30 degrees
Usage: Confirms directional momentum strength in trend-following scenarios
Pressure Surge Signal
Calculation: volSpike_AVP and strongTrendUp_ATG
Purpose: Combines volume expansion with trend confirmation
Characteristics: Requires both volume spike and strong uptrend simultaneously
Usage: bullish signal for trend continuation
Shift Wick Signal
Calculation: ta.crossunder(ema1, ema2) and isWickTrapDetected and directionFlip
Purpose: Detects bearish reversal with wick trap confirmation
Characteristics: Combines EMA crossunder with upper wick dominance and directional flip
Usage: Reversal signal for trend change identification
🛡️ Trap Exit Protection Signals
Bear Trap Exit
Calculation: isUpperWickTrap and isBearEngulfNow
Conditions: Previous bullish candle with 80%+ upper wick, followed by current bearish engulfing
Purpose: Emergency exit signal for long positions
Priority: Highest - overrides all other hold conditions
Action: Immediate position closure with full state reset
Bull Trap Exit
Calculation: isLowerWickTrap and isBullEngulfNow
Conditions: Previous bearish candle with 80%+ lower wick, followed by current bullish engulfing
Purpose: Emergency exit signal for short positions
Priority: Highest - overrides all other hold conditions
Action: Immediate position closure with full state reset
📊 Technical Analysis Foundation Signals
RSI-MFI Hybrid System
Base Calculation: (ta.rsi(close, 14) + ta.mfi(close, 14)) / 2
Oversold Threshold: < 35
Overbought Threshold: > 65
Weak Condition: < 35 and declining
Strong Condition: > 65 and rising
Usage: Momentum confirmation and reversal identification
ADX-DMI Trend Classification
Strong Up Trend: (adx > 25 and diplus > diminus and (diplus - diminus) > 5) or (ema1 > ema2 and ema2 > ema3 and ta.rising(ema2, 3))
Strong Down Trend: (adx > 20 and diminus > diplus - 5) or (ema1 < ema2 and ta.falling(ema1, 3))
Trend Weakening: adx < adx and adx < adx
Usage: Primary trend direction confirmation
Bollinger Band Squeeze Detection
Calculation: bbWidth < ta.lowest(bbWidth, 20) * 1.2
Purpose: Identifies low volatility periods before breakouts
Usage: Entry filter - avoids trades during consolidation
🎨 Visual Signal Indicators
Red X Signal
Calculation: isBearCandle and ta.crossunder(ema1, ema2)
Visual: Red X above price
Purpose: Bearish EMA crossunder with confirming candle
Composite Weight: +1.0 for short positions, -1.0 for long positions
Characteristics: Simple but effective trend change indicator
Green Dot Signal
Calculation: isBullCandle and ta.crossover(ema1, ema2)
Visual: Green dot below price
Purpose: Bullish EMA crossover with confirming candle
Composite Weight: +1.0 for long positions, -1.0 for short positions
Characteristics: Entry confirmation for trend-following strategies
Blue Diamond Signal
Trigger Conditions: amcBuySignal and score >= 4
Scoring Components: 11 different technical conditions
Key Requirements: AMC bullish + momentum rise + EMA expansion + volume confirmation
Visual: Blue diamond below price
Purpose: Bullish reversal or continuation signal
Characteristics: Multi-factor confirmation requiring 4+ technical alignments
Red Diamond Signal
Trigger Conditions: amcSellSignal and score >= 5
Scoring Components: 11 different technical conditions (stricter than Blue Diamond)
Key Requirements: AMC bearish + momentum crash + EMA compression + volume decline
Visual: Red diamond above price
Purpose: Potential bearish reversal or continuation signal
Characteristics: Requires higher threshold (5 vs 4) for more selective triggering
🔵 Specialized Detection Signals
Blue Dot Signal
Calculation: volumePulse and isCandleStrong and volIsHigh
Requirements: Volume > 2.0x MA, strong candle body > 35% of range, volume MA > 55
Purpose: Volume-confirmed momentum signal
Visual: Blue dot above price
Characteristics: Volume-centric signal for high-liquidity environments
Orange X Signal
Calculation: Complex multi-factor oversold reversal detection
Requirements: AMC oversold + wick trap + flash/blink + RSI-MFI oversold + bullish flip
Purpose: Oversold bounce signal with multiple confirmations
Visual: Orange X below price
Characteristics: Reversal signal requiring 5+ simultaneous conditions
VSS (Velocity Signal System)
Components: Volume spike + EMA angle + trend direction
Buy Signal: vssTrigger and vssTrendDir == 1
Sell Signal: vssTrigger and vssTrendDir == -1
Visual: Green/Red triangles
Purpose: Velocity-based momentum detection
Characteristics: Fast-response signal for momentum trading
⭐ Elite Composite Signals
Star Uprising Signal
Base Requirements: entryCompositeBuySignal and echoBodyLong and strongUpTrend and isAMCUp
Additional Confirmations: RSI hybrid strong + not high risk
Special Conditions: At bottom zone OR RSI bottom bounce OR strong volume bounce
Visual: Star symbol below price
Purpose: Bullish reversal signal from oversold conditions
Characteristics: Most selective bullish signal requiring multiple confirmations
Ultra Short Signal
Scoring System: 7-component scoring requiring 4+ points
Key Components: EMA trap + volume decline + RSI weakness + composite confirmation
Additional Requirements: Falling EMA structure + volume spike + flash confirmation
Visual: Explosion emoji above price
Purpose: Aggressive short entry for trend reversal or continuation
Characteristics: Complex multi-layered signal for experienced short selling
🎯 Composite Signal Architecture
Enhanced Composite Scoring
Long Composite: 15+ weighted components including structure, momentum, flash/blink, volume, price action, reversal triggers, trend alignment
Short Composite: Mirror structure with bearish bias
Threshold: 5.0 points required for signal activation
Conflict Resolution: If both long and short signals trigger simultaneously, both are disabled
Final Validation: Requires EMA momentum confirmation (ta.rising(emaFast_ATG, 2) for longs, ta.falling(emaFast_ATG, 2) for shorts)
Risk Assessment Integration
High Risk Long: RSI > 70 OR close > upper Bollinger Band 80%
High Risk Short: RSI < 30 OR close < lower Bollinger Band 80%
Zone Analysis: Top zone (95% of 50-bar high) vs Bottom zone (105% of 50-bar low)
Risk Penalty: High risk conditions subtract 1.5 points from composite scores
This signal architecture creates a multi-layered detection system where simple momentum signals provide foundation, technical analysis adds structure, visual indicators offer clarity, specialized detectors capture different market conditions, and composite signals identify potential opportunities while integrated risk assessment is designed to filter risky entries.
VISUAL FEATURES SHOWCASE
Ichimoku Cloud Visualization
Dynamic Color Intensity: Cloud transparency adapts to momentum strength - darker colors indicate stronger directional moves, while lighter transparency shows weakening momentum phases.
Gradient Color Mapping: Bullish momentum renders blue-purple spectrum with increasing opacity, while bearish momentum displays corresponding color gradients with intensity-based transparency.
Real-time Momentum Feedback: Color saturation provides immediate visual feedback on market structure strength, allowing traders to assess levels at a glance without additional indicators.
EMA Ribbon Bands
The 8-level exponential moving average system creates a comprehensive trend structure map with gradient color coding.
Signal Type Visualization
STRATEGY PROPERTIES & BACKTESTING DISCLOSURE
📊 Default Strategy Configuration:
✅ Initial Capital: 100,000 USD (realistic for average traders)
✅ Commission: 0.075% per trade (realistic exchange fees)
✅ Slippage: 3 ticks (market impact consideration)
✅ Position Size: 5% equity per trade (sustainable risk level)
✅ Pyramiding: Disabled (single position management)
✅ Sample Size: 185 trades over 12-month backtesting period
✅ Risk Management: Adaptive stop loss with maximum 1% risk per trade
COMPREHENSIVE BACKTESTING RESULTS
Testing Period & Market Conditions:
Backtesting Period: June 25, 2024 - June 25, 2025 (12 months)
Timeframe: 15-minute charts (MTF system active)
Market: BTCUSDT (Bitcoin/Tether)
Market Conditions: Full market cycle including volatility periods
Deep Backtesting: Enabled for maximum accuracy
📈 Performance Summary:
Total Return: +2.19% (+2,193.59 USDT)
Total Trades Executed: 185 trades
Win Rate: 34.05% (63 winning trades out of 185)
Profit Factor: 1.295 (gross profit ÷ gross loss)
Maximum Drawdown: 0.65% (653.17 USDT)
Risk-Adjusted Returns: Consistent with conservative risk management approach
📊 Detailed Trade Analysis:
Position Distribution:
Long Positions: 109 trades (58.9%) | Win Rate: 36.70%
Short Positions: 76 trades (41.1%) | Win Rate: 30.26%
Average Trade Duration: Optimized for 15-minute timeframe efficiency
Profitability Metrics:
Average Profit per Trade: 11.74 USDT (0.23%)
Average Winning Trade: 151.17 USDT (3.00%)
Average Losing Trade: 60.27 USDT (1.20%)
Win/Loss Ratio: 2.508 (winners are 2.5x larger than losses)
Largest Single Win: 436.02 USDT (8.69%)
Largest Single Loss: 107.41 USDT (controlled risk management)
💰 Financial Performance Breakdown:
Gross Profit: 9,523.93 USDT (9.52% of capital)
Gross Loss: 7,352.48 USDT (7.35% of capital)
Net Profit After Costs: 2,171.44 USDT (2.17%)
Commission Costs: 1,402.47 USDT (realistic trading expenses)
Maximum Equity Run-up: 2,431.66 USDT (2.38%)
⚖️ Risk Management Validation:
Maximum Drawdown: 0.65% showing controlled risk management
Drawdown Recovery: Consistent equity curve progression
Risk per Trade: Successfully maintained below 1.5% per position
Position Sizing: 5% equity allocation proved sustainable throughout testing period
📋 Strategy Performance Characteristics:
✅ Strengths Demonstrated:
Controlled Risk: Maximum drawdown well below industry standards (< 1%)
Positive Expectancy: Win/loss ratio of 2.5+ creates profitable edge
Consistent Performance: Steady equity curve without extreme volatility
Realistic Costs: Includes actual commission and slippage impacts
Sample Size: 185 trades during testing period
⚠️ Performance Considerations:
Win Rate: 34% win rate requires discipline to follow system signals
Market Dependency: Performance may vary significantly in different market conditions
Timeframe Sensitivity: Optimized for 15-minute charts; other timeframes may show different results
Slippage Impact: Real trading conditions may affect actual performance
📊 Benchmark Comparison:
Strategy Return: +2.19% over 12 months
Buy & Hold Bitcoin: +71.12% over same period
Strategy Advantage: Significantly lower drawdown and volatility
Risk-Adjusted Performance: Different risk profile compared to holding cryptocurrency
🎯 Real-World Application Insights:
Expected Trading Frequency:
Average: 15.4 trades per month (185 trades ÷ 12 months)
Weekly Frequency: Approximately 3-4 trades per week
Active Management: Requires regular monitoring during market hours
Capital Requirements:
Minimum Used in Testing: $10,000 for sustainable position sizing
Tested Range: $50,000-$100,000 for comfortable risk management
Commission Impact: 0.075% per trade totaled 1.4% of capital over 12 months
⚠️ IMPORTANT BACKTESTING DISCLAIMERS:
📈 Performance Reality:
Past performance does not guarantee future results. Backtesting results represent hypothetical performance and may not reflect actual trading outcomes due to market changes, execution differences, and emotional factors.
🔄 Market Condition Dependency:
This strategy's performance during the tested period may not be representative of performance in different market conditions, volatility regimes, or trending vs. sideways markets.
💸 Cost Considerations:
Actual trading costs may vary based on broker selection, market conditions, and trade size. Commission rates and slippage assumptions may differ from real-world execution.
🎯 Realistic Expectations:
The 34% win rate requires psychological discipline to continue following signals during losing streaks. Risk management and position sizing are critical for replicating these results.
⚡ Technology Dependencies:
Strategy performance assumes reliable internet connection, platform stability, and timely signal execution. Technical failures may impact actual results.
CONFIGURATION OPTIMIZATION
5-Minute Timeframe Optimization (Advanced Users Only)
⚠️ Important Warning: 5-minute timeframes operate without MTF confirmation, resulting in reduced signal quality and higher false signal rates.
Example 5-Minute Parameters:
Composite Thresholds: Long 6.5, Short 7.0 (vs 15M default 5.0/5.4)
Signal Lookback Bars: 12 (vs 15M default 8)
Volume Multiplier: 2.2 (vs 15M default 1.8)
MTF Timeframe: Disabled (automatic below 30M)
Risk Management Adjustments:
Position Size: Reduce to 3% (vs 5% default)
TP1: 0.8%, TP2: 1.2%, TP3: 2.0% (tighter targets)
SL: 0.8% (tighter stop loss)
Cooldown Minutes: 8 (vs 5 default)
Usage Notes for 5-Minute Trading:
- Wait for higher composite scores before entry
- Require stronger volume confirmation
- Monitor EMA structure more closely
15-Minute Scalping Setup:
TP1: 1.0%, TP2: 1.5%, TP3: 2.5%
Composite Threshold: 5.0 (higher filtering)
TP ATR Multiplier: 7.0
SL ATR Multiplier: 2.5
Volume Multiplier: 1.8 (requires stronger confirmation)
Hold Time: 2 bars minimum
3-Hour Swing Setup:
TP1: 2.0%, TP2: 4.0%, TP3: 8.0%
Composite Threshold: 4.5 (more signals)
TP ATR Multiplier: 8.0
SL ATR Multiplier: 3.2
Volume Multiplier: 1.2
Hold Time: 6 bars minimum
Market-Specific Adjustments
High Volatility Periods:
Increase ATR multipliers (TP: 2.0x, SL: 1.2x)
Raise composite thresholds (+0.5 points)
Reduce position size
Enable cooldown periods
Low Volatility Periods:
Decrease ATR multipliers (TP: 1.2x, SL: 0.8x)
Lower composite thresholds (-0.3 points)
Standard position sizing
Disable extended cooldowns
News Events:
Temporarily disable strategy 30 minutes before major releases
Increase volume requirements (2.0x multiplier)
Reduce position sizes by 50%
Monitor for unusual price action
RISK MANAGEMENT
Dual ROI System: Adaptive vs Fixed Mode
Adaptive RR Mode:
Uses ATR (Average True Range) for automatic adjustment
TP1: 1.0x ATR from entry price
TP2: 1.5x ATR from entry price
TP3: 2.0x ATR from entry price
Stop Loss: 1.0x ATR from entry price
Automatically adjusts to market volatility
Fixed Percentage Mode:
Uses predetermined percentage levels
TP1: 1.0% (default)
TP2: 1.5% (default)
TP3: 2.5% (default)
Stop Loss: 0.9% total (0.6% risk tolerance + 0.3% slippage buffer)(default)
Consistent levels regardless of volatility
Mode Selection: Enable "Use Adaptive RR" for ATR-based targets, disable for fixed percentages. Adaptive mode works better in varying volatility conditions, while fixed mode provides predictable risk/reward ratios.
Stop Loss Management
In Adaptive SL Mode:
Automatically scales with market volatility
Tight stops during low volatility (smaller ATR)
Wider stops during high volatility (larger ATR)
Include 0.3% slippage buffer in both modes
In Fixed Mode:
Consistent percentage-based stops
2% for crypto, 1.5% for forex, 1% for stocks
Manual adjustment needed for different market conditions
Trailing Stop System
Configuration:
Enable Trailing: Activates dynamic stop loss adjustment
Start Trailing %: Profit level to begin trailing (default 1.0%)
Trailing Offset %: Distance from current price (default 0.5%)
Close if Return to Entry: Optional immediate exit if price returns to entry level
Operation: Once position reaches trailing start level, stop loss automatically adjusts upward (longs) or downward (shorts) maintaining the offset distance from favorable price movement.
Timeframe-Specific Risk Considerations
15-Minute and Above (Tested):
✅ Full MTF system active
✅ Standard risk parameters apply
✅ Backtested performance metrics valid
✅ Standard position sizing (5%)
5-Minute Timeframes (Advanced Only):
⚠️ MTF system inactive - local signals only
⚠️ Higher false signal rate expected
⚠️ Reduced position sizing preferred (3%)
⚠️ Tighter stop losses required (0.8% vs 1.2%)
⚠️ Requires parameter optimization
⚠️ Monitor performance closely
1-Minute Timeframes (Limited Testing):
❌ Excessive noise levels
❌ Strategy not optimized for this frequency
Risk Management Practices
Allocate no more than 5% of your total investment portfolio to high-risk trading
Never trade with funds you cannot afford to lose
Thoroughly backtest and validate the strategy with small amounts before full implementation
Always maintain proper risk management and stop-loss settings
IMPORTANT DISCLAIMERS
Performance Disclaimer
Past performance does not guarantee future results. All trading involves substantial risk of loss. This strategy is provided for informational purposes and does not constitute financial advice.
Market Risk
Cryptocurrency and forex markets are highly volatile. Prices can move rapidly against positions, resulting in significant losses. Users should never risk more than they can afford to lose.
Strategy Limitations
This strategy relies on technical analysis and may not perform well during fundamental market shifts, news events, or unprecedented market conditions. No trading strategy can guarantee 100% success or eliminate the risk of loss.
Legal Compliance
You are responsible for compliance with all applicable regulations and laws in your jurisdiction. Consult with licensed financial professionals when necessary.
User Responsibility
Users are responsible for their own trading decisions, risk management, and compliance with applicable regulations in their jurisdiction.
ATR Dynamic Stop (Table + Plot + ATR %)📊 This script displays dynamic stop levels based on ATR, designed for active traders.
Features:
- Shows long and short stop levels (price ± ATR × multiplier).
- Displays values as a floating table on the top-right corner.
- Optional plot lines directly on the chart.
- Option to calculate based on realtime price or last close.
- Displays the ATR value both in price units and as a percentage of the selected price.
- Fully customizable table: text size, text color, background color.
Inputs:
- ATR Multiplier and Length.
- Show/hide stop lines on the chart.
- Select price source (realtime or last close).
- Table appearance options.
Ideal for:
- Traders who want a clear visual stop guide.
- Combining volatility with risk management.
52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix====== 52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix ======
◆ Overview
52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix is an advanced multi-band indicator that integrates Bollinger Bands, Fibonacci levels, and ATR-based Spike signals (for detecting bullish/bearish pressure and volatility surges).
Built on a VWMA (Volume-Weighted Moving Average) foundation, it displays standard deviation bands, Fibonacci extension zones, multi-level expansions, and real-time bullish/bearish spike alerts alongside price labeling and color gradation.
This tool is designed to help traders visually analyze and react to:
- Key support/resistance zones
- Overbought/oversold boundaries
- Sudden directional volatility shifts (spikes)
All parameters are customizable to suit a wide variety of trading strategies and styles.
====== ◆ Key Features ======
- Multi-structured Bollinger Bands: VWMA-based center line with ± standard deviation bands and multiple levels of outer extension (+10% to +50%)
- Integrated Fibonacci Bands: Levels at 23.6%, 38.2%, 50%, 61.8%, and 78.6% above and below the center line
- ATR-based Spike Signal Alerts: Automatically detects sudden bullish/bearish volatility surges and triggers directional warning labels (“Bullish Spike Warning” or “Bearish Spike Warning”)
- Real-Time Price Labels & Visual Gradation: Each important band and level includes live price labeling and color-coded zone visualization
- Fully Adjustable Parameters & Panel Display Options: All inputs and visual elements can be toggled or customized
====== ◆ Technical Basis ======
■ Bollinger Bands & Multi-Extension
- Center Line: VWMA (Volume-Weighted Moving Average)
- Bands: ± Standard deviation (default 2.5), with extensions in +10% increments up to +50%
- Extension Zones: Reveal reactions to high volatility or trend continuation
■ Fibonacci Bands
- Symmetrical expansion from center line using Fibonacci ratios
- Visually highlights layered historical retracement zones and price clustering
■ ATR-Based Spike Signal
- Adaptive to chart timeframe (ATR Length & Multiplier auto-adjusted)
- Spike alerts triggered when price exceeds upper/lower ATR bands
- One signal per X bars to filter noise (interval adjustable)
■ Live Visual Labeling & Color Gradients
- Intelligently labeled bands with dynamic color shading between levels
- Helps clarify price geometry and zone importance
====== ◆ Practical Applications ======
■ Spike Signal Interpretation
- Bullish Spike Warning — Market plunged below ATR range → Potential oversold rebound signal
- Bearish Spike Warning — Market surged above ATR range → Potential overbought reversal signal
■ Band & Level Interaction
- Ripple behavior between Fibonacci levels signals trend momentum/weakness
- Penetration through outer expansion bands flags possible trend strength or volatility spikes
■ Integrated Trading Strategies
- Reversal Trades: Bounces between extension and Fibonacci levels
- Breakout Confirmation: Spike signals backing breakout moves
- Directional Bias: Trend-following confirmation when price exceeds multiple zones
====== ◆ Advanced Setting Options ======
All parameters can be fine-tuned for your trading strategy, market, and timeframe.
■ Bollinger Band Period
_Default:_ 20
_Description:_ Number of bars for VWMA and standard deviation. Shorter (10–14): faster but noisier. Longer (30–50): smoother, better for trend analysis.
■ Standard Deviation Multiplier
_Default:_ 2.5
_Description:_ Controls main band width. Lower values (1.5–2.0): More signals, higher sensitivity. Higher values (2.5–3.0): Fewer signals, higher reliability.
■ Band Extension Ratios
_Default:_ +10%, +20%, +30%, +40%, +50%
_Description:_ Amount to expand beyond standard bands. Used for detecting extended zones or extreme price movement areas.
■ ATR Length
_Default:_ Auto depending on timeframe (typically 14–30)
_Description:_ Period for calculating ATR. Shorter: Reacts faster, more sensitive. Longer: Smoother, filters short noise.
■ ATR Multiplier
_Default:_ Auto (1.75 to 2.8)
_Description:_ Sets the threshold for Spike signals. Lower: More frequent but smaller spikes. Higher: Triggers fewer but stronger signals.
■ Fibonacci Levels
_Default:_ 0.236, 0.382, 0.5, 0.618, 0.786
_Description:_ Determines how far Fibonacci bands extend from the center. Aids in identifying key retracement and reaction points.
■ Spike Signal Interval
_Default:_ 7 bars
_Description:_ Minimum bar separation between consecutive spike signals. Prevents signal overflooding from consecutive candles.
■ Labels & Coloring Display
_Toggle ON/OFF_
Show/hide all price labels and visual zone shading. Useful for decluttering or focusing on strategy testing.
Try adjusting these inputs based on your strategy and market conditions. Optimize for scalping, swing trading, day trading, or investing by testing different lengths, bands, and spike sensitivities.
====== ◆ Indicator Synergies ======
- Combine with moving averages, RSI, or MACD for breakout filters
- Use with support/resistance lines or Fibonacci retracements to validate critical zones
- Pair with Keltner Channels, ATR Bands, or volume-based tools for enhanced volatility tracking
====== ◆ Conclusion ======
52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix offers a cohesive framework that connects price level analysis, trend structure, and volatility-driven directional signals—all in one indicator. It’s not just a visualization tool, but a decision-support system for both reactive trade entries and proactive risk management. With full parameter adjustability and a clear structural layout, it empowers traders to adapt across assets, timeframes, and strategies—efficiently and confidently.
====== ◆ Disclaimer ======
This indicator is for informational and educational purposes only.
Past performance does not guarantee future results. Always apply proper risk management.
====== 52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix ======
◆ 개요
52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix는 볼린저 밴드, 피보나치 레벨, ATR 기반 스파이크 신호(상방/하방 압력 감지)를 결합한 고급 멀티 밴드 인디케이터입니다.
VWMA(거래량 가중 이동평균) 기반 중심선 위에 표준편차 밴드, 피보나치 확장 레벨, 다중 확장 밴드, 실시간 상·하방 스파이크 경고(라벨)와 가격 레이블·컬러 그라데이션이 동시에 제공됩니다.
트레이더가 주요 지지/저항, 과매수·과매도, 급격한 변동성 스파이크(방향성 돌파)를 한눈에 시각적으로 분석할 수 있도록 디자인되었습니다.
모든 설정값은 트레이딩 스타일에 맞춰 자유롭게 조절 가능합니다.
====== ◆ 주요 특징 ======
- VWMA 기반 중심선과 표준편차 밴드(±), 10~50% 단계별 외곽 확장
- 피보나치 밴드: 중심선 기준 23.6%, 38.2%, 50%, 61.8%, 78.6% 상·하단 동시 표기
- ATR 기반 스파이크 신호: 강한 상·하방 변동성 구간 실시간 감지(‘Bullish Spike Warning’, ‘Bearish Spike Warning’ 라벨)
- 실시간 가격 레이블 & 컬러 구간 구분
- 밴드/변동성/피보나치/시각 옵션 등 설정 완전 자유화
====== ◆ 기술적 기반 ======
■ 볼린저 밴드/확장
- VWMA 중심선, ± 표준편차 밴드(기본 2.5), 단계별 외곽 확장(10~50%)
■ 피보나치 밴드
- 중심선 기준 대칭 배치(0.236, 0.382, 0.5, 0.618, 0.786)
■ ATR 기반 스파이크 신호
- 차트 주기에 자동 최적화(ATR 기간/배수), 상단·하단 ATR 밴드 돌파 시 스파이크 라벨
- 반복 신호 방지(신호 간격 조정 가능)
■ 실시간 레이블 & 컬러 그라데이션
- 주요 밴드, 피보나치, 확장 레벨별 가격 표시 및 구간 별도 색상
====== ◆ 실용적 응용 ======
■ 스파이크 신호 해석
- Bullish Spike Warning: 과매도 구간(강한 하락 후 단기 반등 가능성)
- Bearish Spike Warning: 과매수 구간(급등 이후 단기 되돌림 가능성)
■ 밴드 & 레벨 시그널
- 피보나치 레벨 간 파동/추세 강도 진단
- 외곽 확장 밴드 돌파 시 강한 추세 혹은 변동성 집중 구간 인식
■ 통합 트레이딩 전략
- 주요 밴드·피보나치 간 바운스, 전환 패턴 기반 반전매매
- 스파이크 신호와 결합한 돌파 추종·추세 확정 대응
- 다중 구간 통과 시 방향성 강화 신호 등급별 분할 대응
====== ◆ 고급 설정 옵션 ======
트레이딩 스타일, 차트 주기, 시장 환경에 따라 모든 항목을 직접 조정할 수 있습니다.
■ 볼린저 밴드 기간 (Bollinger Band Period)
기본값: 20
VWMA 및 표준편차 산출에 적용할 캔들 수
짧게(10~14): 신호 빠르며 노이즈 많음
길게(30~50): 깔끔한 추세 중시
■ 표준편차 계수 (Standard Deviation Multiplier)
기본값: 2.5
밴드 폭 조절
1.5~2.0: 민감, 많이 신호
2.5~3.0: 신뢰도 높고 드문 신호
■ 밴드 확장 비율 (Band Extension Ratios)
기본값: 10%, 20%, 30%, 40%, 50%
기본 밴드에서 외곽 확장 단계
극단 변동성, 피로구간 등 감지
■ ATR 기간 (ATR Length)
기본값: 자동(보통 14~30)
ATR 산출 캔들 수
짧을수록 민감, 길수록 부드러움
■ ATR 배수 (ATR Multiplier)
기본값: 자동(1.75~2.8)
스파이크 신호 감지 문턱값
낮게: 잦고 약한 신호
높게: 드문 강한 신호
■ 피보나치 레벨 (Fibonacci Levels)
기본값: 0.236, 0.382, 0.5, 0.618, 0.786
중심선으로부터 각 밴드 거리
주요 지지/저항, 파동구조 세분화
■ 스파이크 신호 간격 (Spike Signal Interval)
기본값: 7
연속적 신호 과다 방지용 최소 캔들 수
높을수록 과발생 차단
■ 레이블/채색 표시 (Labels & Coloring)
On/Off
가격 레이블·영역 컬러 표시 ON/OFF
시장/전략별로 세부 세팅을 바꿔가며 직접 테스트 해보세요!
====== ◆ 시너지 활용 ======
- 이동평균, RSI, MACD 등과 조합시 신호 필터링
- 기존 수평 지지/저항, 피보나치 리트레이스먼트 등과 병용
- ATR, 켈트너밴드, 거래량 등과 복합 분석 가능
====== ◆ 결론 ======
52SIGNAL RECIPE Bollinger Bands & Fibonacci Spike Signal Matrix는 가격 구조, 변동성 이벤트, 방향성 신호를 하나로 통합한 고급 매매 지원 시스템입니다.
스캘핑, 스윙, 포지션 트레이딩 등 다양한 전략에 맞게 모든 파라미터를 세밀하게 조율할 수 있습니다.
현대 트레이딩 환경에 최적화된 정밀 결정 지원 도구로 활용하세요.
====== ◆ 면책 조항 ======
본 지표는 정보 제공 및 교육 목적입니다.
과거 실적이 미래의 수익을 보장하지 않으므로 반드시 철저한 리스크 관리를 병행하세요.
ATR Trailing Stop with ATR Targets [v6]What the Indicator Does
This custom TradingView indicator is designed for active traders who want to automate and visualize their trailing stop management and target setting, using true market volatility. It combines the Average True Range (ATR) with dynamic market structure logic to:
Trail a stop-loss behind major swings in real time, using 2×ATR (adjustable) from the highest high in uptrends or the lowest low in downtrends.
Flip trading bias between bullish and bearish when the stop is breached.
Identify and plot three profit targets (at 1, 2, and 3 ATR from the breakout/flip point) after every stop-flip, helping traders scale out or set take-profits objectively.
Maintain a visible presence on your chart every bar to avoid indicator errors, with color and labeling for clear distinction between long/short phases.
How the Indicator Works
1. ATR Calculation
ATR Period and Multiplier: You select your preferred ATR length (default is 14 bars) and a multiplier (default is 2.0).
Volatility Adjustment: ATR measures the average "true" bar range, so the trailing stop and targets adapt to current volatility.
2. Trailing Stop Logic
Uptrend (bullish bias): The indicator tracks the highest high made since the last bearish-to-bullish flip and sets the stop at - .
The stop only raises (never lowers) during an uptrend, protecting gains in strong moves.
Downtrend (bearish bias): Tracks the lowest low made since the last bullish-to-bearish flip, with stop at + .
The stop only lowers (never raises) in a downtrend.
Flip Point: If price closes through the trailing stop, the current bias “flips,” and the logic reverses (bullish to bearish or vice versa). At the new close, flip price and bar index are stored for target calculation.
3. ATR Targets after Flip
After each stop flip:
Three targets—based on the new close price—are calculated and plotted:
Long flip (new bull bias): Target1 = close + 1×ATR, Target2 = close + 2×ATR, Target3 = close + 3×ATR.
Short flip (new bear bias): Target1 = close - 1×ATR, Target2 = close - 2×ATR, Target3 = close - 3×ATR.
These targets help with scaling out, partial profit-taking, or setting automated orders.
4. Visual Feedback
Trailing stop line: Green for long bias, red for short bias.
Targets: Distinct color-coded circles at 1, 2, 3 ATR levels from the most recent flip.
Flip Labels: Mark the bar and price where bias flipped (“Long Flip” or “Short Flip”) for quick pattern recognition.
Subtle background shading: Ensures TradingView's requirement for “indicator output every bar.”
How to Use This Indicator
Parameter Setup
ATR Period and Multiplier: Adjust to match the timeframe and volatility of your instrument.
Lower periods/multipliers for short-term/volatile trading.
Higher values for smoother signals or higher timeframes.
Starting Trend: Set to match the expected initial bias if the instrument has strong trend characteristics.
Trading Application
1. Daily Bias Approach
Establish your bias in line with your trading plan (e.g., only trade long if price is above the previous day's high, short below the previous day's low).
Only look for trades in the indicator's current bias direction, as expressed by the stop and background color.
2. Entry
Use the indicator as a real-time confirmation or trailing stop for your entries.
Breakout: Enter when price establishes the current bias, using the trailing stop as your risk level.
Reversal: Wait for a bias flip after an extended move; enter in the direction of the new bias.
VWAP Rebound: Combine with a VWAP bounce—enter only if the indicator bias supports your direction.
3. Exits/Targets
Trailing stop management: Move your stop according to the plotted line; exit if your stop is hit.
Profit-taking: Scale out or take profits as price approaches each ATR-based target.
Use the dynamic labeling to identify reversal flips and reset your plan if stopped or the bias changes.
4. Market Context
Filter and frame setups by watching correlated indicators (DXY, VIX, AUDJPY, put/call ratio) and upcoming news; trade only in the daily bias direction for best consistency.
5. Practical Tips
Combine this indicator with your custom watchlist and alert settings to get notified on flips or targets.
Review the last label ("Long Flip"/"Short Flip") and targets to plan partial exits.
Remember: ATR adapts to volatility, so the stop and targets stay proportionate even when price action shifts.
Moving Average / ATR Breakout Signal [ARTech]Moving Average / ATR Breakout Signal
This indicator generates trend-following signals based on price breaking above or below a user-defined Moving Average (MA). It supports various MA types and lengths, while offering optional filters like ATR bands and breakout thresholds to enhance signal quality. The tool is designed to help traders detect momentum shifts with configurable confirmation logic and offers visual enhancements to help traders better interpret market conditions at a glance.
Key Features:
• Multi-Type Moving Average Support: Choose from various Moving Average types including EMA, SMA, Hull MA, VWMA, RMA, TEMA, and more — fully customizable with source and length options.
• Flexible Signal Logic: Signals are generated when price breaks above or below the selected MA. You can define the number of confirmation candles and choose between wick-based or close-based break logic.
• ATR-Based Filtering: Enable ATR filtering to create dynamic upper and lower breakout bands around the MA. This helps reduce noise and validate true breakouts with volatility-adjusted thresholds.
• Breakout Threshold Filtering: Add an optional breakout condition where the price must first move a minimum percentage away from the previous signal level before a new opposite signal is allowed. Prevents choppy back-to-back signals.
• Visual Enhancements: Color-coded backgrounds highlight long and short zones, adapting dynamically to signal context. Optional MA slope coloring further supports trend visualization.
• Signal Alerts: Customizable alerts for long and short signals, including user-defined messages, to keep you notified in real-time.
Why use this indicator?
• Helps you identify clear trend shifts by focusing on price action relative to a customizable moving average.
• Improves signal reliability with optional ATR filtering and breakout confirmation, reducing false signals.
• Flexible MA types and lengths let you tailor the indicator to your trading style.
• Suitable for traders of all levels looking for a straightforward, yet powerful trend-following tool.
How to Use
███████ Alerts ███████
• Custom Alerts: To enable Custom Alerts, you need to activate the fx alert() function call option in TradingView’s alert creation dialog. Then, select the desired alert type (Long or Short) from the indicator's settings under the "Alerts" section, you can customize messages and enable notifications for Long and Short signals.
Using Custom Alerts allows you to set up one alert that covers both Long and Short signals, simplifying your alert management.
• Long and Short Alerts: To create Long or Short alerts, open the alert dialog, select this indicator as the condition, then choose “Long” or “Short” from the list and click Create.
You need to set up two separate alerts: one for Long signals and one for Short signals.
███████ Moving Average ███████
This is the core component of the signal system. You can customize:
Moving Average Type: Choose from SMA, EMA, WMA, Hull MA, VWMA, RMA, or TEMA
Length: Adjust the length to suit your strategy.
Source: Select which price data (e.g., Close, Open, HL2) is used to calculate the MA.
Show Slope Color: Colors the MA line based on its direction: upward slopes are shown in the selected "Up" color, while downward slopes use the "Down" color. This helps you visually confirm trend direction at a glance.
Show Background Color: When enabled, highlights the area between the MA and price to enhance signal zones:
– If ATR filter is on, the space between ATR bands is shaded.
– If ATR filter is off, the area between the MA line and bar closes is colored.
This helps emphasize potential breakout or trend-following zones visually.
███████ Break Options ███████
Confirm Candles: Defines the number of consecutive candles that must break the selected level to confirm a signal.
– If ATR filter is enabled, this level is the ATR bands.
– If ATR is disabled, the Moving Average line is used.
This helps filter out noise and avoid premature signals.
Break Type: Specifies how the candle must break the level:
– Close: The candle must close beyond the level.
– Wick: A wick touching or exceeding the level is enough.
Choose based on how strict you want the breakout condition to be.
███████ Filters ███████
This section provides optional filters to improve signal accuracy:
ATR
When enabled, breakout confirmation requires the price to cross above the upper breakout line or below the lower breakout line by a specified percentage from the last signal price.
• Multiplier: Adjusts the width of ATR bands by multiplying the ATR value.
• Length: Sets the period for ATR calculation.
• Smoothing: Selects the smoothing method applied to the ATR (RMA, SMA, EMA, WMA).
• Upper and Lower Line Colors: Customize the colors of the ATR bands.
Breakout Filter
When enabled, breakout confirmation requires the price to cross above the upper breakout line or below the lower breakout line by a specified percentage from the last signal price.
• Threshold (%): Defines the minimum percentage price movement required to validate a breakout.
• Show Breakout Levels: Toggle to display or hide breakout threshold area on the chart.
ADR TableTrack volatility and session momentum in real-time with customizable precision.
Key Features:
Average Daily Range (ADR): Configurable length (default 5 days), based on previous daily high–low ranges.
Session Anchor Options: Choose anchor at 4 am NY, 6 pm NY, 9:30 am NY, 8:30 am NY, Previous Day Close, or Current Bar.
Session Range & %ADR: Displays the real-time range from the chosen anchor, plus what percentage of ADR has been covered.
High / Low Target Levels: Calculates ADR targets based on anchor: anchor ± ADR.
Optional Target Lines: Draw horizontal lines for high and low targets across the session; customize color and width.
Dynamic Table Display: User-selectable table size and text size (Tiny to Huge) for optimal readability.
Robust Anchor Logic: Uses the first bar at-or-after anchor time each NY day, ensuring stability even on irregular intraday timeframes.
How to Use
Choose your anchor in settings.
View ADR, session range (with %ADR), and target price levels in the top-right pane.Toggle High/Low lines to overlay targets on the chart.
Adjust table and text size to match your workspace.
Why It Matters
Quickly assess where price stands relative to typical volatility.
Easily identify intraday price exhaustion or breakout zones.
Anchor flexibility enables use for both futures and equities, aligning with your trading session.
Clean, professional display—no clutter, no guesswork.
ATR Trailing + Alerts + Price LabelsATR Trend is a clean and intelligent trend-following overlay built for traders who want clarity during both trending and ranging markets.
This indicator dynamically detects bullish and bearish market trends using the Average True Range (ATR), applying a confirmation-based approach to filter out false signals and minor pullbacks.
The trend line is:
Blue 🔵 during uptrends.
Black ⚫ during downtrends.
Continuous, recalculating only when the market truly shifts — not just when price temporarily crosses the line.
When a confirmed trend reversal occurs:
A 🔼 or 🔽 label shows the exact price of the flip.
An alert can be triggered to notify the user immediately.
💡 Features:
✅ Single-line trend direction
✅ Filters out short-term noise
✅ Exact price labeling on trend change
✅ Built-in alerts for up/down trend shifts
⚙️ Inputs:
ATR Period – Length of ATR calculation (default: 14)
ATR Multiplier – Offset for trend line placement (default: 2.0)
Flip Sensitivity – Number of bars required to confirm a trend reversal (default: 3)
This tool is suitable for:
Swing traders avoid false breakouts
Scalpers looking for high-probability trend entries
Algorithmic setups requiring structured trend logic
Risk Distribution HistogramStatistical risk visualization and analysis tool for any ticker 📊
The Risk Distribution Histogram visualizes the statistical distribution of different risk metrics for any financial instrument. It converts risk data into histograms with quartile-based color coding, so that traders can understand their risk, tail-risks, exposure patterns and make data-driven decisions based on empirical evidence rather than assumptions.
The indicator supports multiple risk calculation methods, each designed for different aspects of market analysis, from general volatility assessment to tail risk analysis.
Risk Measurement Methods
Standard Deviation
Captures raw daily price volatility by measuring the dispersion of price movements. Ideal for understanding overall market conditions and timing volatility-based strategies.
Use case: Options trading and volatility analysis.
Average True Range (ATR)
Measures true range as a percentage of price, accounting for gaps and limit moves. Valuable for position sizing across different price levels.
Use case: Position sizing and stop-loss placement.
The chart above illustrates how ATR statistical distribution can be used by looking at the ATR % of price distribution. For example, 90% of the movements are below 5%.
Downside Deviation
Only considers negative price movements, making it ideal for checking downside risk and capital protection rather than capturing upside volatility.
Use case: Downside protection strategies and stop losses.
Drawdown Analysis
Tracks peak-to-trough declines, providing insight into maximum loss potential during different market conditions.
Use case: Risk management and capital preservation.
The chart above illustrates tale risk for the asset (TQQQ), showing that it is possible to have drawdowns higher than 20%.
Entropy-Based Risk (EVaR)
Uses information theory to quantify market uncertainty. Higher entropy values indicate more unpredictable price action, valuable for detecting regime changes.
Use case: Advanced risk modeling and tail-risk.
VIX Histogram
Incorporates the market's fear index directly into analysis, showing how current volatility expectations compare to historical patterns. The CAPITALCOM:VIX histogram is independent from the ticker on the chart.
Use case: Volatility trading and market timing.
Visual Features
The histogram uses quartile-based color coding that immediately shows where current risk levels stand relative to historical patterns:
Green (Q1): Low Risk (0-25th percentile)
Yellow (Q2): Medium-Low Risk (25-50th percentile)
Orange (Q3): Medium-High Risk (50-75th percentile)
Red (Q4): High Risk (75-100th percentile)
The data table provides detailed statistics, including:
Count Distribution: Historical observations in each bin
PMF: Percentage probability for each risk level
CDF: Cumulative probability up to each level
Current Risk Marker: Shows your current position in the distribution
Trading Applications
When current risk falls into upper quartiles (Q3 or Q4), it signals conditions are riskier than 50-75% of historical observations. This guides position sizing and portfolio adjustments.
Key applications:
Position sizing based on empirical risk distributions
Monitoring risk regime changes over time
Comparing risk patterns across timeframes
Risk distribution analysis improves trade timing by identifying when market conditions favor specific strategies.
Enter positions during low-risk periods (Q1)
Reduce exposure in high-risk periods (Q4)
Use percentile rankings for dynamic stop-loss placement
Time volatility strategies using distribution patterns
Detect regime shifts through distribution changes
Compare current conditions to historical benchmarks
Identify outlier events in tail regions
Validate quantitative models with empirical data
Configuration Options
Data Collection
Lookback Period: Control amount of historical data analyzed
Date Range Filtering: Focus on specific market periods
Sample Size Validation: Automatic reliability warnings
Histogram Customization
Bin Count: 10-50 bins for different detail levels
Auto/Manual Bin Width: Optimize for your data range
Visual Preferences: Custom colors and font sizes
Implementation Guide
Start with Standard Deviation on daily charts for the most intuitive introduction to distribution-based risk analysis.
Method Selection: Begin with Standard Deviation
Setup: Use daily charts with 20-30 bins
Interpretation: Focus on quartile transitions as signals
Monitoring: Track distribution changes for regime detection
The tool provides comprehensive statistics including mean, standard deviation, quartiles, and current position metrics like Z-score and percentile ranking.
Enjoy, and please let me know your feedback! 😊🥂
Average Daily Range ADR by thSpecial for Amer and ATR testing and some text for description which I will add a little bit later because beatiful tv can't pass my indicator to be published
UT Bot + LinReg Candles (Dual Sensitivity)
Script Description:
This indicator combines the popular UT Bot Alerts system with Linear Regression Candles (open source) for enhanced trend detection and trading signals in one singel script. The UT Bot features independent, then 2 x ATR sensitivity and periods controls for buy and sell signals, allowing you to fine-tune entries and exits to match your strategy. The script also overlays colored Linear Regression Candles with an optional signal line, helping you visually identify trend strength and direction. All calculations are performed on standard chart prices (no Heikin Ashi). Suitable for all asset classes and timeframes.
Eample setting for usdjpy 5 min chart for repeated buy and sell singnals based on trend:
BUY ATR period 300 multiplier 1
SELL ATR period 1 multiplier 2
Disclaimer:
This script is for informational and educational purposes only. It is not financial advice. Use at your own risk; the author assumes no responsibility for any trading results or losses.
Credits goes to to Ugurvu for linreg candles and quantnomad for UT Bot alerts that make this script possible.
Author: Patrick
